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9d8dc0318b
2706 Commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
Rui Liu
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9d8dc0318b |
[pruning] add rowwise counter to sparse adagrad
Summary: Use the newly added counter op in sparse adagrad Reviewed By: chocjy, ellie-wen Differential Revision: D19221100 fbshipit-source-id: d939d83e3b5b3179f57194be2e8864d0fbbee2c1 |
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Eileen Pan
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4102fbdf08 |
[1/n] Allow dense NaN value in dper raw input processor output
Summary: ## TLDR Support using NaN default value for missing dense features in RawInputProcessor for *DPER2*. In preparation for subsequent support for null flag features in *compute meta*. For train_eval this is already supported in DPER3 and we do not plan to support this in DPER2 train eval. ## Overview Intern project plan to support adding dense flags for missing feature values instead of replacing with zero. Project plan : https://docs.google.com/document/d/1OsPUTjpJycwxWLCue3Tnb1mx0uDC_2KKWvC1Rwpo2NI/edit?usp=sharing ## Code paths: See https://fb.quip.com/eFXUA0tbDmNw for the call stack for all affected code paths. Test Plan: # A. DPER3 blob value inspection ## 1. Build local bento kernel in fbcode folder `buck build mode/dev-nosan //bento/kernels:bento_kernel_ads_ranking` ## 2. Use kernel `ads_ranking (local)` to print dense feature blob values n280239 ## 2.1 Try `default_dense_value = "0.0"` (default) ``` preproc_6/feature_preproc_6/dper_feature_processor_7/raw_input_proc_7/float_feature_sparse_to_dense_7/float_features [[0. ] [0. ] [0. ] [0. ] [0. ] [0. ] [0. ] [1. ] [1.7857143] [1.7777778] [1. ] [0. ] [0.5625 ] [0. ] [0. ] [0.8 ] [0. ] [1. ] [0.56 ] [0. ]] ``` ## 2.2 Try `default_dense_value = "123"` ``` preproc_2/feature_preproc_2/dper_feature_processor_3/raw_input_proc_3/float_feature_sparse_to_dense_3/float_features [[123. ] [123. ] [123. ] [123. ] [123. ] [123. ] [123. ] [ 1. ] [ 1.7857143] [ 1.7777778] [ 1. ] [123. ] [ 0.5625 ] [123. ] [123. ] [ 0.8 ] [123. ] [ 1. ] [ 0.56 ] [123. ]] ``` ## 2.3 Try `default_dense_value = float("nan")` ``` RuntimeError: [enforce fail at enforce_finite_op.h:40] std::isfinite(input_data[i]). Index 0 is not finite (e.g., NaN, Inf): -nan (Error from operator: input: "unary_4/logistic_regression_loss_4/average_loss_4/average_loss" name: "" type: "EnforceFinite" device_option { random_seed: 54 }) ``` which is expected due to nan input. # B. Unit test `buck test fblearner/flow/projects/dper/tests/preprocs:raw_feature_extractor_test` https://www.internalfb.com/intern/testinfra/testconsole/testrun/5348024586274923/ {F241336814} Differential Revision: D21961595 fbshipit-source-id: 3dcb153b3c7f42f391584f5e7f52f3d9c76de31f |
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peter
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e2201e2ed8 |
Fixes caffe2 loading issues on Windows (#39513)
Summary: Addresses https://github.com/pytorch/pytorch/issues/27840#issuecomment-638715422. Contains a bunch of fixes (https://github.com/pytorch/pytorch/pull/39376 + https://github.com/pytorch/pytorch/pull/39334 + https://github.com/pytorch/pytorch/pull/38302 + https://github.com/pytorch/pytorch/pull/35362) Pull Request resolved: https://github.com/pytorch/pytorch/pull/39513 Differential Revision: D22190761 Pulled By: malfet fbshipit-source-id: b2d52f6cb16c233d16071e9c0670dfff7da2710e |
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Neha Shah
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5ad885b823 |
[Caffe2][Pruning] Make the caffe2 Sum operator support long types (#40379)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/40379 The current sum operator doesn't support Long .. hence modify the code Test Plan: Write a test case Reviewed By: jspark1105, yinghai Differential Revision: D21917365 fbshipit-source-id: b37d2c100c70d17d2f89c309e40360ddfab584ee |
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Jongsoo Park
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7a837019a4 |
[caffe2] optimize 2/4-bit row-wise quantization (#387)
Summary: Pull Request resolved: https://github.com/pytorch/FBGEMM/pull/387 Pull Request resolved: https://github.com/pytorch/pytorch/pull/39985 avx2 optimized 2/4-bit row-wise quantization/dequantization in perfkernels. This diff slightly change the numerics of quantization by multiplying with the inverse of scale instead of dividing with scale. Test Plan: In my devserver for i in 2 4 8; do echo $i; buck run mode/opt :fused_rowwise_nbit_conversion_bench -- --bit-rate=$i; done Before this diff 2-bit 3.35394 ms. 100%. FloatToFused2BitRowwiseQuantized 4-bit 3.60351 ms. 100%. FloatToFused4BitRowwiseQuantized 8-bit 0.434467 ms. 100%. FloatToFused8BitRowwiseQuantized After this diff 2-bit 0.606386 ms. 100%. FloatToFused2BitRowwiseQuantized 4-bit 0.446683 ms. 100%. FloatToFused4BitRowwiseQuantized 8-bit 0.4349 ms. 100%. FloatToFused8BitRowwiseQuantized Reviewed By: choudharydhruv, jianyuh Differential Revision: D22033195 fbshipit-source-id: d3a219e47b8345268d90a160c9314ed0d5b71467 |
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Yinghai Lu
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3ea15af630 |
[Onnxifi] Allow adding timeout for OnnxifOp run (#40081)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/40081 Adding the functionality to enable timeout of OnnxifiOp run. In the case of backend hanging, it can error out quickly. Test Plan: ``` buck test glow/fb/test:test_onnxifinnpi -- test_timeout ``` Reviewed By: jackm321 Differential Revision: D22064533 fbshipit-source-id: 25487287c10ab217eb95692f09d48e13e19436ab |
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Hongzheng Shi
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f6b0fbe2c5 |
topk tensor k support (#39407)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/39407 - support passing a single element tensor as k for topk module - support passing a single element tensor to constant fill output Test Plan: buck test dper3/dper3/modules/tests:core_modules_test -- test_topk_gating_without_split_examples_tensor_k buck test caffe2/caffe2/python:hypothesis_test -- test_constant_fill_from_tensor Reviewed By: huayuli00 Differential Revision: D21843739 fbshipit-source-id: 0c5f5c03e9f57eeba40c0068784625164c2527ec |
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Jeff Daily
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1e05e5e0ae |
Correct #39759 for HIP. (#39801)
Summary: Changes in PR https://github.com/pytorch/pytorch/issues/39759 broke HIP caffe2. hipify for caffe2 renames CUDA to HIP; torch does not. If caffe2 calls into torch, it needs to use CUDA-named functions. CC ezyang xw285cornell sunway513 houseroad dzhulgakov Pull Request resolved: https://github.com/pytorch/pytorch/pull/39801 Differential Revision: D21982493 Pulled By: xw285cornell fbshipit-source-id: 8e88e0fb80c71f0342e23ef0214a42d5542bdc70 |
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Dmytro Dzhulgakov
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1f027ac02d |
Disable testTHCAllocator on HIP (#39843)
Summary: THCAllocator functionality is pretty obscure and it's hard to get it working with HIP because of how Caffe2/PyTorch rules are set up (see https://github.com/pytorch/pytorch/issues/39801). Let's just disable the test. Pull Request resolved: https://github.com/pytorch/pytorch/pull/39843 Reviewed By: zou3519 Differential Revision: D21998687 Pulled By: dzhulgakov fbshipit-source-id: cd12ba30cdfee658b98393ed3a72e83f4ecf1c9c |
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Taiqing Wang
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ad91a3a11f |
Skipping L2 regularization on sparse biases
Summary: # Motivations As explained in the [link](https://stats.stackexchange.com/questions/86991/reason-for-not-shrinking-the-bias-intercept-term-in-regression/161689#161689), regularizing biases will cause mis-calibration of predicted probabilities. In SparseNN, the unary processor may use 1d embedding tables for the sparse features to serve as biases. In this diff, the regularization term is automatically skipped for the 1d sparse parameters to avoid regularizing biases. # Experiments Experiments were conducted to verify that it has no significant impact on the NE to skip the regularization on 1d sparse parameters. Baseline.1 (no L2 regularization): f193105372 Baseline.2 (L2 regularization in prod): f193105522 Treatment (skipping L2 regularization on 1d sparse params): f193105708 {F239859690} Test Plan: Experiments were conducted to verify that it has no significant impact on the NE to skip the regularization on 1d sparse parameters using a canary package: `aml.dper2.canary:9efc576b35b24361bb600dcbf94d31ea`. Baseline.1 (no L2 regularization): f193105372 Baseline.2 (L2 regularization in prod): f193105522 Treatment (skipping L2 regularization on 1d sparse params): f193105708 Reviewed By: zhongyx12 Differential Revision: D21757902 fbshipit-source-id: ced126e1eab270669b9981c9ecc287dfc9dee995 |
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Jongsoo Park
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262dbdf0a5 |
[caffe2/nomnigraph] handle when PATH env is not defined (#39373)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/39373 Line 114 is the only actual change. Other changes are just formatting. Test Plan: CI Reviewed By: zrphercule Differential Revision: D21830893 fbshipit-source-id: 83e49b1b3c48f6bc6de3c48ccce60c84aa49339b |
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Dmytro Dzhulgakov
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e46060701d |
[caffe2] Fix of initializing ATen's CUDA before using caching allocator (#39759)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/39759 Caffe2 has a mode where it uses PT's caching allocator. Somehow we were not calling the initialization explicitly. Now, I have no idea why it worked before. Probably worth to run a bisect separately. Reviewed By: houseroad Differential Revision: D21962331 fbshipit-source-id: f16ad6b27a67dbe0bda93939cca8c94620d22a09 |
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Jamie King
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2633a9cca1 |
Adding LpNorm regularization for sparse features in DPER3 (#38582)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/38582 Adding LpNorm regularization for sparse features in DPER3. This is done using a sparse regularization op with run_after_optimizer (see D21003029). * Added code calling new caffe2 operator from D21003029 to caffe2/python/regularizer.py * Added l1norm and l2norm to sparse regularizer thrift definition. * Added the new regularization references to test utils. * Added a new file for unit tests "sparse_nn_sparse_reg_test.py" Test Plan: buck test mode/dev //caffe2/caffe2/fb/dper/layer_models/tests:sparse_nn_sparse_reg_test buck test mode/dev //caffe2/caffe2/fb/dper/layer_models/tests:sparse_nn_reg_test DPER canary: https://fburl.com/fblearner/rcp5yzeh New DPER canary: https://fburl.com/fblearner/0krgd74x Differential Revision: D20704248 fbshipit-source-id: 7e3d5013b3ff3da95ea027f0f2dd855f3ae8e41d |
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Chunli Fu
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834569232b |
[online trainer] Add blob reorder (#39534)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/39534 Reviewed By: boryiingsu Differential Revision: D21871352 fbshipit-source-id: 00cce83b7351fdafd36d4db57c99fb8a58e8a260 |
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Nikita Shulga
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e2a178ca21 |
Update cafe2 hypothesis_test_util to support hypothesis-5 (#39498)
Summary: Extracting forward-backward `hypothesis` interface update parts of https://github.com/pytorch/pytorch/pull/39430 into a separate PR Pull Request resolved: https://github.com/pytorch/pytorch/pull/39498 Differential Revision: D21900210 Pulled By: malfet fbshipit-source-id: 75e637cf839f49dc141d37e1686ce45ff4721245 |
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Lu Fang
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15ad9dd30f |
[ONNX] Bump up ONNX submodule to a82c6a7010e2e332d8f74ad5b0c726fd47c85376 (#39372)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/39372 we only bump the submodule in oss to unblock some works Test Plan: ci Reviewed By: hl475 Differential Revision: D21830800 fbshipit-source-id: fb4a716992efcd71926f7bba24a7c24422c17e38 |
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Jongsoo Park
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fca928cabf |
[caffe2] fix test error in video_input_op_test (#39382)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/39382 Test Plan: buck test caffe2/caffe2/python/operator_test:video_input_op_test Reviewed By: dutran Differential Revision: D21832355 fbshipit-source-id: 47b1b0610b9600437fe1ed317d5af47d624767fb |
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Jongsoo Park
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04ac41fe70 |
[caffe2] format video_input_op_test.py (#39381)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/39381 To prepare D21832355 Test Plan: Just formatting Reviewed By: dutran Differential Revision: D21832354 fbshipit-source-id: bbf6a1377752adaa115ee2e2a5ba546964e3fd08 |
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Jamie King
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7f1a96d43c |
Adding sparse Lp regularization operator to Caffe2 (#38574)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/38574 Adding sparse L1 and L2 regularization operator to Caffe2. This doesn't work using run_on_loss, only run_after_optimize. Applying it to run_after_optimize rather than run_on_loss was easier to implement, particularly for the L1 norm which is preferable in some cases and is non-differentiable at zero. Test Plan: Wrote and ran unit tests in operator_test:sparse_lp_regularizer_test. Differential Revision: D21003029 fbshipit-source-id: 81070a621752560ce03e320d065ce27807a5d278 |
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Xiaodong Wang
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fcef43965b |
[AMD] Fix broken test (#39297)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/39297 histogram op doesn't have GPU implementation. It's breaking the CI GPU test. Make the test run cpu only. Test Plan: CI Reviewed By: hwangjeff Differential Revision: D21800824 fbshipit-source-id: 9c835786f22bac7d420ce610397a6ee69084c19a |
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Jeff Hwang
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0b9d537056 |
[dper][pruning] add histogram op (#38514)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/38514 this diff introduces the `Histogram` caffe2 op, which computes a histogram tensor for a list of input tensors. the bin edges of the histogram are defined by arg `bin_edges`. Test Plan: tests Reviewed By: chocjy Differential Revision: D21553956 fbshipit-source-id: fc98c8db691d66d2dad57b6ad14867109913cb6f |
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Lu Fang
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90a8cdfdbf |
Automatic update of fbcode/onnx to eae3eb8c61cf5ad27cc9a416dbdc5274982385a6 (#39089)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/39089 Previous import was 79a7e0df7e86e0f32e7a05f563b24a566540c18b Included changes: - **[eae3eb8c](https://github.com/onnx/onnx/commit/eae3eb8c)**: Use cmake GNUInstallDirs (#2661) <Gustavo Alvarez> - **[106821e9](https://github.com/onnx/onnx/commit/106821e9)**: Update sequence test case so input is not scalar and splits are specified (#2675) <Scott McKay> - **[e094e101](https://github.com/onnx/onnx/commit/e094e101)**: Remove unnecessary copies and std::move (#2684) <Changming Sun> - **[71145275](https://github.com/onnx/onnx/commit/71145275)**: Update Batchnorm test (#2674) <Lara Haidar> - **[da13be2d](https://github.com/onnx/onnx/commit/da13be2d)**: Rename OPTIONAL to OPTIONAL_VALUE (#2682) <Changming Sun> - **[2987fa06](https://github.com/onnx/onnx/commit/2987fa06)**: Adding CI for ONNX Debug mode (Linux, OSX) (#2651) <Vinitra Swamy> - **[46fe392d](https://github.com/onnx/onnx/commit/46fe392d)**: Update Pow input types in Opset 12 (#2666) <Lara Haidar> - **[ac1caf3b](https://github.com/onnx/onnx/commit/ac1caf3b)**: Change type of label tensor to int32/int64 in SoftmaxCrossEntropyLoss spec. (#2667) <M. Zeeshan Siddiqui> - **[c2fefcbf](https://github.com/onnx/onnx/commit/c2fefcbf)**: [Training] SG with Momentum Optimizer (#1959) <Wei-Sheng Chin> - **[8d15705e](https://github.com/onnx/onnx/commit/8d15705e)**: [Training] Add Adagrad optimizer operator (#1955) <Wei-Sheng Chin> - **[94b01cdd](https://github.com/onnx/onnx/commit/94b01cdd)**: Suppress a warning in unsqueeze (#2637) <Hong Xu> - **[0582d526](https://github.com/onnx/onnx/commit/0582d526)**: Fix Greater/LessOrEqual function definition (#2645) <Takeshi Watanabe> - **[b852d819](https://github.com/onnx/onnx/commit/b852d819)**: Increment version number to 1.7.0 (#2639) <Chin Huang> - **[ff4bb553](https://github.com/onnx/onnx/commit/ff4bb553)**: Regenerate Min test data (#2644) <Takeshi Watanabe> Test Plan: ci Reviewed By: hl475 Differential Revision: D21750299 fbshipit-source-id: c33ec1b1e0dc65d0187e78db96d749f9037aae9c |
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Natalia Gimelshein
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93d87a16eb |
Revert D21493165: Automatic update of fbcode/onnx to 20b3e10e6c3a9cdab90d2bb864d1c36d3e3651cd
Test Plan: revert-hammer Differential Revision: D21493165 Original commit changeset: 6863b289bfbf fbshipit-source-id: 47b530c8ffceb3673a86b6cf0c064fe6af0eb72d |
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Lu Fang
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51274b501a |
Automatic update of fbcode/onnx to 20b3e10e6c3a9cdab90d2bb864d1c36d3e3651cd (#38203)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/38203 Previous import was 79a7e0df7e86e0f32e7a05f563b24a566540c18b Included changes: - **[20b3e10e](https://github.com/onnx/onnx/commit/20b3e10e)**: Add 'ignore_index' input in the spec for SoftmaxCrossEntropyLoss and NLLLoss. (#2680) <M. Zeeshan Siddiqui> - **[eae3eb8c](https://github.com/onnx/onnx/commit/eae3eb8c)**: Use cmake GNUInstallDirs (#2661) <Gustavo Alvarez> - **[106821e9](https://github.com/onnx/onnx/commit/106821e9)**: Update sequence test case so input is not scalar and splits are specified (#2675) <Scott McKay> - **[e094e101](https://github.com/onnx/onnx/commit/e094e101)**: Remove unnecessary copies and std::move (#2684) <Changming Sun> - **[71145275](https://github.com/onnx/onnx/commit/71145275)**: Update Batchnorm test (#2674) <Lara Haidar> - **[da13be2d](https://github.com/onnx/onnx/commit/da13be2d)**: Rename OPTIONAL to OPTIONAL_VALUE (#2682) <Changming Sun> - **[2987fa06](https://github.com/onnx/onnx/commit/2987fa06)**: Adding CI for ONNX Debug mode (Linux, OSX) (#2651) <Vinitra Swamy> - **[46fe392d](https://github.com/onnx/onnx/commit/46fe392d)**: Update Pow input types in Opset 12 (#2666) <Lara Haidar> - **[ac1caf3b](https://github.com/onnx/onnx/commit/ac1caf3b)**: Change type of label tensor to int32/int64 in SoftmaxCrossEntropyLoss spec. (#2667) <M. Zeeshan Siddiqui> - **[c2fefcbf](https://github.com/onnx/onnx/commit/c2fefcbf)**: [Training] SG with Momentum Optimizer (#1959) <Wei-Sheng Chin> - **[8d15705e](https://github.com/onnx/onnx/commit/8d15705e)**: [Training] Add Adagrad optimizer operator (#1955) <Wei-Sheng Chin> - **[94b01cdd](https://github.com/onnx/onnx/commit/94b01cdd)**: Suppress a warning in unsqueeze (#2637) <Hong Xu> - **[0582d526](https://github.com/onnx/onnx/commit/0582d526)**: Fix Greater/LessOrEqual function definition (#2645) <Takeshi Watanabe> - **[b852d819](https://github.com/onnx/onnx/commit/b852d819)**: Increment version number to 1.7.0 (#2639) <Chin Huang> - **[ff4bb553](https://github.com/onnx/onnx/commit/ff4bb553)**: Regenerate Min test data (#2644) <Takeshi Watanabe> Test Plan: ci Reviewed By: hl475 Differential Revision: D21493165 fbshipit-source-id: 6863b289bfbf4235e36f0e2456ce44c776aaf164 |
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Yan Zhu
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c40a79a027 |
[c2] cuda impl for WeightScale op (#38712)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/38712 as title Test Plan: buck test; Reviewed By: ustctf Differential Revision: D21586705 fbshipit-source-id: 12cd34f04f074ee12b77304055f3ba6068cf38fb |
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Yan Zhu
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dfbf9f397f |
Back out "Back out "[c2] register cuda op for LpNorm (fallback)"" (#38566)
Summary: Previously we got a CI issue in original submission (D21562485), so we backout the original diff (D21588831). Resubmitting here to reprod the CI issue and ask caffe2 dev to take a look. Pull Request resolved: https://github.com/pytorch/pytorch/pull/38566 Original commit changeset: 6dda4b71904d Test Plan: buck test Reviewed By: houseroad Differential Revision: D21589352 fbshipit-source-id: de40ff2884019e14476e31c4c952f24d6e438f5f |
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Nirav Mehta
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acacad2575 |
Adding support for manifold files in DBReader (#37727)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/37727 Check if the file exists locally only for `log_file_db` db_type. Reader files in other `db_type` like `manifold_log_file_db` are excluded from this check. Test Plan: Verified that files stored in manifold can be loaded using `DBFileReader`. Reviewed By: hbjerry Differential Revision: D21329671 fbshipit-source-id: bbc0e88851783ca3f78f7c61bfe84b480c09b5ac |
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Yan Zhu
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3d0532f3ab |
[c2] fix compute_norm test (#38529)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/38529 (Note: this ignores all push blocking failures!) Test Plan: buck test mode/opt //caffe2/caffe2/python/modeling:compute_norm_for_blobs_test Reviewed By: olittle Differential Revision: D21588603 fbshipit-source-id: bdb0ae455e85a934cb5e369fbb0078f2ff842814 |
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Yan Zhu
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fac9f36563 |
Back out "[c2] register cuda op for LpNorm (fallback)"
Summary: Original commit changeset: 573419e5a8da Test Plan: D21562485 breaks CI build. Unlanding Reviewed By: olittle Differential Revision: D21588831 fbshipit-source-id: 6dda4b71904d7765f32f570f9722e4a9a6cbc97b |
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Yan Zhu
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0e0b9496fe |
[c2] [easy] stop gradient when diagnose (#38518)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/38518 as title Test Plan: buck test Reviewed By: olittle Differential Revision: D21562570 fbshipit-source-id: 3a2e8dea3d821a2bdb9f30db25816a2bfa6c5dcf |
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Yan Zhu
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bbfd0ef244 |
[c2] register cuda op for LpNorm (fallback) (#38517)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/38517 as title Test Plan: buck test Reviewed By: olittle Differential Revision: D21562485 fbshipit-source-id: 573419e5a8dae4121d99d5b72ed3960a92db7a54 |
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Jongsoo Park
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6be3e5d3bb |
[caffe2] weight_decay in reduced precision adagrad
Summary: As title Test Plan: CI Reviewed By: taiqing Differential Revision: D21512729 fbshipit-source-id: 0777c90954ebad0cbd5785460e7b2a7c8c146316 |
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Tao Wu
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08c3339e7c |
[pyfi] override TP2 networkx -> PyFI networkx (#37764)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/37764 Auto-generated diff for TP2->PyFI migration. ``` networkx TP2 version: 2.0 PyFI active wheels (networkx): py2-darwin -> 2.3 py2-platform007 -> 2.2 py3-darwin -> 2.3 py3-platform007 -> 2.3 py3.7-platform007 -> 2.3 ``` #buildmore excited_python Test Plan: buildallthethings Reviewed By: thatch Differential Revision: D19790867 fbshipit-source-id: d6f893beee794df5408a5117978b534cafc6ec83 |
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Lu Fang
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8181711637 |
Automatic update of fbcode/onnx to 79a7e0df7e86e0f32e7a05f563b24a566540c18b (#38106)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/38106 Previous import was 807c62cf7e4c96ce49040bcf073b7e4a054f28a5 Included changes: - **[79a7e0df](https://github.com/onnx/onnx/commit/79a7e0df)**: Fix copy paste error of Min op test case (#2640) <Takeshi Watanabe> - **[4cd2538d](https://github.com/onnx/onnx/commit/4cd2538d)**: Add a release pipeline for Windows python packages (#2632) <Changming Sun> - **[e8b33a5a](https://github.com/onnx/onnx/commit/e8b33a5a)**: Adding UnfoldToDepth op [1.7 Release] (#2616) <Negin Raoof> - **[c2a8d525](https://github.com/onnx/onnx/commit/c2a8d525)**: update docs (#2627) <Ksenija Stanojevic> - **[22752354](https://github.com/onnx/onnx/commit/22752354)**: Generate tests for MeanSquareDistance and SoftmaxCrossEntropyLoss (#2623) <Jonny Shipton> - **[602bd622](https://github.com/onnx/onnx/commit/602bd622)**: Add section about external tensor data to IR.md (#2323) <Jonny Shipton> - **[165c3f3b](https://github.com/onnx/onnx/commit/165c3f3b)**: Add integer support to Clip (#2532) <Jonny Shipton> - **[a5fabf87](https://github.com/onnx/onnx/commit/a5fabf87)**: Add operators LessOrEqual and GreaterOrEqual (as functions) (#2606) <Jeremy Cochoy> - **[f1dcdafc](https://github.com/onnx/onnx/commit/f1dcdafc)**: Fix input document of quantized operators (#2117) <Takeshi Watanabe> - **[43af9b69](https://github.com/onnx/onnx/commit/43af9b69)**: Add reference impl for sequence ops (#2380) <Bowen Bao> - **[aa50aa12](https://github.com/onnx/onnx/commit/aa50aa12)**: Print value case of TypeProto more friendly (#2422) <Takeshi Watanabe> - **[2e67bfc3](https://github.com/onnx/onnx/commit/2e67bfc3)**: Fix issue #2436 (#2447) <daquexian> - **[d27ffc6b](https://github.com/onnx/onnx/commit/d27ffc6b)**: Add support for integer tensors to Min and Max (#2608) <Jonny Shipton> - **[5cc668af](https://github.com/onnx/onnx/commit/5cc668af)**: Update IR.md to describe training extension. (#2615) <G. Ramalingam> - **[8c5bf9d4](https://github.com/onnx/onnx/commit/8c5bf9d4)**: Generate node backend tests for celu operator (#2607) <Jonny Shipton> - **[7b65287e](https://github.com/onnx/onnx/commit/7b65287e)**: Change dtype of dd_da in gradient test to float32 (#2620) <Shinichiro Hamaji> - **[e91739f2](https://github.com/onnx/onnx/commit/e91739f2)**: Introduce SoftmaxCrossentropy as a loss function (#2573) <Ksenija Stanojevic> - **[b008ed3a](https://github.com/onnx/onnx/commit/b008ed3a)**: Support gathernd with batch_dim mode (#2585) <wezuo> - **[d2fe4f22](https://github.com/onnx/onnx/commit/d2fe4f22)**: Introduce MeanSquaredError as Loss Function (#2570) <Ksenija Stanojevic> - **[10b812a6](https://github.com/onnx/onnx/commit/10b812a6)**: Add support for default attributes within FunctionExpandHelper (#2588) <Ewa Tusień> - **[3368834c](https://github.com/onnx/onnx/commit/3368834c)**: adding version update content. (#2609) <Ke Zhang> - **[8873cb02](https://github.com/onnx/onnx/commit/8873cb02)**: Adding Inverse Op (#2578) <Negin Raoof> Test Plan: ci Reviewed By: hl475 Differential Revision: D21471424 fbshipit-source-id: 5009a5f9558458a0aba56b2a9e8fffc3895a9e02 |
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Lu Fang
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3cade9cdd4 |
Automatic update of fbcode/onnx to 807c62cf7e4c96ce49040bcf073b7e4a054f28a5 (#37983)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/37983 Previous import was 9fdae4c68960a2d44cd1cc871c74a6a9d469fa1f Included changes: - **[807c62cf](https://github.com/onnx/onnx/commit/807c62cf)**: Training Proposal: Spec Changes and Gradient Operator (#2314) <Wei-Sheng Chin> Test Plan: ci Reviewed By: hl475 Differential Revision: D21441188 fbshipit-source-id: 88b5be5bd479b59bdb45525f5dfe61d787151cdd |
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Lu Fang
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9efbc19f75 |
Fix the issue with C2 cont build
Summary: Issue was introduced in D21258652. We need to make sure it compiles with opt mode. We may still have some left over py2 packages. Let's just use some format work with both. Test Plan: ci Reviewed By: xush6528 Differential Revision: D21457394 fbshipit-source-id: cde79a0fc6b4feba307bd9d45e1a1d4a42de9263 |
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Nikita Shulga
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952e0f00a4 |
Skip c2_ref_tests on network failures (#37972)
Summary: Skip the tests if network is unaccessible and model can not be downloaded Pull Request resolved: https://github.com/pytorch/pytorch/pull/37972 Differential Revision: D21441996 Pulled By: malfet fbshipit-source-id: 5ce59764584974aee9195572338ada1fa0351a75 |
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Quang Luong
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9d7a79ac27 |
[Caffe2] raise exceptions instead of str (#37744)
Summary: Some exceptions are not correctly wrapped inside a class. Pull Request resolved: https://github.com/pytorch/pytorch/pull/37744 Differential Revision: D21388197 Pulled By: mrshenli fbshipit-source-id: 2d69e2543c2e05116c367d137968b982c254d2dc |
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Jeff Daily
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4a2c642e1f |
fix ROCm bench CI by increasing first iter timeout (#37633)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/37633 Differential Revision: D21395519 Pulled By: ngimel fbshipit-source-id: 03b31417dde0758db6c189c21b6cb5771c776115 |
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Taiqing Wang
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8cb1f2f9dc |
implement L2 regularization for Adagrad in caffe2 and dper (#37705)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/37705 Pull Request resolved: https://github.com/pytorch/pytorch/pull/37372 Posted note: [Regularizing SparseNN Against Over-fitting](https://fb.workplace.com/notes/taiqing-wang/regularizing-sparsenn-against-over-fitting/220306075902708/) **Problem formulation** L(w) = J(w) + lambda/2 * ||w||^2 J(w) is the empirical loss, and ||w||^2 is the squared L2 norm of the parameters, a.k.a. L2 regularizer. dL(w)/ dw_i = dJ(w)/dw_i + lambda w_i dL(w)/ dw_i is the gradient of L(w) w.r.t. w_i. To implement the L2 regularizer, the gradient of J(w) w.r.t. w_i is added with w_i. lambda is called as weight decay in this implementation. **Code changes** * In the initialization method of AdagradOptimizer, a new input argument, weight_decay, is added. * In the _run function of AdagradOptimizer, the weight decay will be skipped for 1d bias vectors. * In the parameter update functions of Adagrad, the gradient is updated by weight_decay * w_i. The default value for weight_decay is zero. Test Plan: ` buck build caffe2/caffe2/fb/dper/layer_models/tests/split_1:sparse_nn_test_weight_decay ` ` ./buck-out/gen/caffe2/caffe2/fb/dper/layer_models/tests/split_1/sparse_nn_test_weight_decay#binary.par ` Reviewed By: jspark1105 Differential Revision: D21258652 fbshipit-source-id: d2366ddcd736a03205a2d16f914703b16d9fce8f |
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Huayu Li
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cd4c3b48a6 |
Add LN after specialzied output embeddings and flexible LCE (#35178)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/35178 * add layer norm (LN) after specialized output embeddings * add flexible lce inside specialized module Test Plan: * unit-tests * buck test caffe2/caffe2/fb/dper/layer_models/tests/split_1:sparse_nn_test_4 -- * buck test caffe2/caffe2/fb/dper/layer_models/tests/split_1:sparse_nn_test_6 -- * workflows * flexible lce: f177025325 {F232112501} * LN: f177025301 {F232112982} Differential Revision: D20586281 fbshipit-source-id: 664e77cb4cb5bec6646cafd2e4afb88aff27df03 |
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Lu Fang
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1aedc2c5b9 |
Skip c2 ref onnx model tests (#37591)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/37591 skip the tests since gluster is gone. Test Plan: ci Reviewed By: ezyang Differential Revision: D21330359 fbshipit-source-id: a4e158fb72eddb08ba49fcfa9541569a150f8481 |
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Ralf Gommers
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78d5707041 |
Fix type annotations and make MyPy run on torch/ (#36584)
Summary: This PR fixes a couple of syntax errors in `torch/` that prevent MyPy from running, fixes simple type annotation errors (e.g. missing `from typing import List, Tuple, Optional`), and adds granular ignores for errors in particular modules as well as for missing typing in third party packages. As a result, running `mypy` in the root dir of the repo now runs on: - `torch/` - `aten/src/ATen/function_wrapper.py` (the only file already covered in CI) In CI this runs on GitHub Actions, job Lint, sub-job "quick-checks", task "MyPy typecheck". It should give (right now): `Success: no issues found in 329 source files`. Here are the details of the original 855 errors when running `mypy torch` on current master (after fixing the couple of syntax errors that prevent `mypy` from running through): <details> ``` torch/utils/tensorboard/_proto_graph.py:1: error: Cannot find implementation or library stub for module named 'tensorboard.compat.proto.node_def_pb2' torch/utils/tensorboard/_proto_graph.py:2: error: Cannot find implementation or library stub for module named 'tensorboard.compat.proto.attr_value_pb2' torch/utils/tensorboard/_proto_graph.py:3: error: Cannot find implementation or library stub for module named 'tensorboard.compat.proto.tensor_shape_pb2' torch/utils/backcompat/__init__.py:1: error: Cannot find implementation or library stub for module named 'torch._C' torch/for_onnx/__init__.py:1: error: Cannot find implementation or library stub for module named 'torch.for_onnx.onnx' torch/cuda/nvtx.py:2: error: Cannot find implementation or library stub for module named 'torch._C' torch/utils/show_pickle.py:59: error: Name 'pickle._Unpickler' is not defined torch/utils/show_pickle.py:113: error: "Type[PrettyPrinter]" has no attribute "_dispatch" torch/utils/tensorboard/_onnx_graph.py:1: error: Cannot find implementation or library stub for module named 'tensorboard.compat.proto.graph_pb2' torch/utils/tensorboard/_onnx_graph.py:2: error: Cannot find implementation or library stub for module named 'tensorboard.compat.proto.node_def_pb2' torch/utils/tensorboard/_onnx_graph.py:3: error: Cannot find implementation or library stub for module named 'tensorboard.compat.proto.versions_pb2' torch/utils/tensorboard/_onnx_graph.py:4: error: Cannot find implementation or library stub for module named 'tensorboard.compat.proto.attr_value_pb2' torch/utils/tensorboard/_onnx_graph.py:5: error: Cannot find implementation or library stub for module named 'tensorboard.compat.proto.tensor_shape_pb2' torch/utils/tensorboard/_onnx_graph.py:9: error: Cannot find implementation or library stub for module named 'onnx' torch/contrib/_tensorboard_vis.py:10: error: Cannot find implementation or library stub for module named 'tensorflow.core.util' torch/contrib/_tensorboard_vis.py:11: error: Cannot find implementation or library stub for module named 'tensorflow.core.framework' torch/contrib/_tensorboard_vis.py:12: error: Cannot find implementation or library stub for module named 'tensorflow.python.summary.writer.writer' torch/utils/hipify/hipify_python.py:43: error: Need type annotation for 'CAFFE2_TEMPLATE_MAP' (hint: "CAFFE2_TEMPLATE_MAP: Dict[<type>, <type>] = ...") torch/utils/hipify/hipify_python.py:636: error: "object" has no attribute "items" torch/nn/_reduction.py:27: error: Name 'Optional' is not defined torch/nn/_reduction.py:27: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Optional") torch/nn/_reduction.py:47: error: Name 'Optional' is not defined torch/nn/_reduction.py:47: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Optional") torch/utils/tensorboard/_utils.py:17: error: Skipping analyzing 'matplotlib.pyplot': found module but no type hints or library stubs torch/utils/tensorboard/_utils.py:17: error: Skipping analyzing 'matplotlib': found module but no type hints or library stubs torch/utils/tensorboard/_utils.py:18: error: Skipping analyzing 'matplotlib.backends.backend_agg': found module but no type hints or library stubs torch/utils/tensorboard/_utils.py:18: error: Skipping analyzing 'matplotlib.backends': found module but no type hints or library stubs torch/nn/modules/utils.py:27: error: Name 'List' is not defined torch/nn/modules/utils.py:27: note: Did you forget to import it from "typing"? (Suggestion: "from typing import List") caffe2/proto/caffe2_pb2.py:17: error: Unexpected keyword argument "serialized_options" for "FileDescriptor"; did you mean "serialized_pb"? caffe2/proto/caffe2_pb2.py:25: error: Unexpected keyword argument "serialized_options" for "EnumDescriptor" caffe2/proto/caffe2_pb2.py:31: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:35: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:39: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:43: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:47: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:51: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:55: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:59: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:63: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:67: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:71: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:75: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:102: error: Unexpected keyword argument "serialized_options" for "EnumDescriptor" caffe2/proto/caffe2_pb2.py:108: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:112: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:124: error: Unexpected keyword argument "serialized_options" for "EnumDescriptor" caffe2/proto/caffe2_pb2.py:130: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:134: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:138: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:142: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:146: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:150: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:154: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:158: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:162: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:166: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:170: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:174: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:178: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:182: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:194: error: Unexpected keyword argument "serialized_options" for "EnumDescriptor" caffe2/proto/caffe2_pb2.py:200: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:204: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:208: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:212: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:224: error: Unexpected keyword argument "serialized_options" for "EnumDescriptor" caffe2/proto/caffe2_pb2.py:230: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:234: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:238: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:242: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:246: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:250: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:254: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/caffe2_pb2.py:267: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/caffe2_pb2.py:274: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:281: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:288: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:295: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:302: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:327: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/caffe2_pb2.py:334: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:341: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:364: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/caffe2_pb2.py:371: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:378: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:385: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:392: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:399: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:406: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:413: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:420: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:427: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:434: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:441: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:448: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:455: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:462: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:488: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/caffe2_pb2.py:495: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:502: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:509: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:516: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:523: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:530: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:537: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:544: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:551: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:558: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:565: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:572: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:596: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/caffe2_pb2.py:603: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:627: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/caffe2_pb2.py:634: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:641: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:648: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:655: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:662: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:686: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/caffe2_pb2.py:693: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:717: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/caffe2_pb2.py:724: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:731: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:738: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:763: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/caffe2_pb2.py:770: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:777: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:784: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:808: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/caffe2_pb2.py:815: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:822: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:829: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:836: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:843: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:850: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:857: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:864: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:871: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:878: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:885: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:892: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:916: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/caffe2_pb2.py:923: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:930: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:937: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:944: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:951: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:958: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:982: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/caffe2_pb2.py:989: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:996: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1003: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1010: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1017: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1024: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1031: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1038: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1045: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1052: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1059: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1066: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1090: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/caffe2_pb2.py:1097: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1104: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1128: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/caffe2_pb2.py:1135: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1142: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1166: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/caffe2_pb2.py:1173: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1180: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1187: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1194: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1218: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/caffe2_pb2.py:1225: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1232: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1239: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1246: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1253: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1260: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1267: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1274: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1281: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1305: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/caffe2_pb2.py:1312: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1319: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1326: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1333: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1340: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1347: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1354: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1361: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1368: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1375: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1382: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1389: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1396: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1420: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/caffe2_pb2.py:1427: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1434: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1441: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1465: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/caffe2_pb2.py:1472: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1479: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1486: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1493: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1500: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1507: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1514: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1538: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/caffe2_pb2.py:1545: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1552: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1559: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1566: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/caffe2_pb2.py:1667: error: "GeneratedProtocolMessageType" has no attribute "Segment" torch/multiprocessing/queue.py:4: error: No library stub file for standard library module 'multiprocessing.reduction' caffe2/proto/torch_pb2.py:18: error: Unexpected keyword argument "serialized_options" for "FileDescriptor"; did you mean "serialized_pb"? caffe2/proto/torch_pb2.py:27: error: Unexpected keyword argument "serialized_options" for "EnumDescriptor" caffe2/proto/torch_pb2.py:33: error: Unexpected keyword argument "serialized_options" for "EnumValueDescriptor" caffe2/proto/torch_pb2.py:50: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/torch_pb2.py:57: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:81: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/torch_pb2.py:88: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:95: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:102: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:109: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:116: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:123: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:130: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:137: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:144: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:151: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:175: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/torch_pb2.py:182: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:189: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:196: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:220: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/torch_pb2.py:227: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:234: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:241: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:265: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/torch_pb2.py:272: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:279: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:286: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:293: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:300: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:307: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:314: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:321: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:328: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:335: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:342: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:366: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/torch_pb2.py:373: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:397: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/torch_pb2.py:404: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:411: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:418: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:425: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/torch_pb2.py:432: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/metanet_pb2.py:17: error: Unexpected keyword argument "serialized_options" for "FileDescriptor"; did you mean "serialized_pb"? caffe2/proto/metanet_pb2.py:29: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/metanet_pb2.py:36: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/metanet_pb2.py:43: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/metanet_pb2.py:50: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/metanet_pb2.py:57: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/metanet_pb2.py:64: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/metanet_pb2.py:88: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/metanet_pb2.py:95: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/metanet_pb2.py:102: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/metanet_pb2.py:126: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/metanet_pb2.py:133: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/metanet_pb2.py:140: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/metanet_pb2.py:164: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/metanet_pb2.py:171: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/metanet_pb2.py:178: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/metanet_pb2.py:202: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/metanet_pb2.py:209: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/metanet_pb2.py:216: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/metanet_pb2.py:240: error: Unexpected keyword argument "serialized_options" for "Descriptor" caffe2/proto/metanet_pb2.py:247: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/metanet_pb2.py:254: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/metanet_pb2.py:261: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/metanet_pb2.py:268: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/metanet_pb2.py:275: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/metanet_pb2.py:282: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/metanet_pb2.py:289: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/metanet_pb2.py:296: error: Unexpected keyword argument "serialized_options" for "FieldDescriptor" caffe2/proto/__init__.py:13: error: Skipping analyzing 'caffe2.caffe2.fb.session.proto': found module but no type hints or library stubs torch/multiprocessing/pool.py:3: error: No library stub file for standard library module 'multiprocessing.util' torch/multiprocessing/pool.py:3: note: (Stub files are from https://github.com/python/typeshed) caffe2/python/scope.py:10: error: Skipping analyzing 'past.builtins': found module but no type hints or library stubs caffe2/python/__init__.py:7: error: Module has no attribute "CPU" caffe2/python/__init__.py:8: error: Module has no attribute "CUDA" caffe2/python/__init__.py:9: error: Module has no attribute "MKLDNN" caffe2/python/__init__.py:10: error: Module has no attribute "OPENGL" caffe2/python/__init__.py:11: error: Module has no attribute "OPENCL" caffe2/python/__init__.py:12: error: Module has no attribute "IDEEP" caffe2/python/__init__.py:13: error: Module has no attribute "HIP" caffe2/python/__init__.py:14: error: Module has no attribute "COMPILE_TIME_MAX_DEVICE_TYPES"; maybe "PROTO_COMPILE_TIME_MAX_DEVICE_TYPES"? caffe2/python/__init__.py:15: error: Module has no attribute "ONLY_FOR_TEST"; maybe "PROTO_ONLY_FOR_TEST"? caffe2/python/__init__.py:34: error: Item "_Loader" of "Optional[_Loader]" has no attribute "exec_module" caffe2/python/__init__.py:34: error: Item "None" of "Optional[_Loader]" has no attribute "exec_module" caffe2/python/__init__.py:35: error: Module has no attribute "cuda" caffe2/python/__init__.py:37: error: Module has no attribute "cuda" caffe2/python/__init__.py:49: error: Module has no attribute "add_dll_directory" torch/random.py:4: error: Cannot find implementation or library stub for module named 'torch._C' torch/_classes.py:2: error: Cannot find implementation or library stub for module named 'torch._C' torch/onnx/__init__.py:1: error: Cannot find implementation or library stub for module named 'torch._C' torch/hub.py:21: error: Skipping analyzing 'tqdm.auto': found module but no type hints or library stubs torch/hub.py:24: error: Skipping analyzing 'tqdm': found module but no type hints or library stubs torch/hub.py:27: error: Name 'tqdm' already defined (possibly by an import) torch/_tensor_str.py:164: error: Not all arguments converted during string formatting torch/_ops.py:1: error: Cannot find implementation or library stub for module named 'torch._C' torch/_linalg_utils.py:26: error: Name 'Optional' is not defined torch/_linalg_utils.py:26: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Optional") torch/_linalg_utils.py:26: error: Name 'Tensor' is not defined torch/_linalg_utils.py:63: error: Name 'Tensor' is not defined torch/_linalg_utils.py:63: error: Name 'Optional' is not defined torch/_linalg_utils.py:63: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Optional") torch/_linalg_utils.py:70: error: Name 'Optional' is not defined torch/_linalg_utils.py:70: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Optional") torch/_linalg_utils.py:70: error: Name 'Tensor' is not defined torch/_linalg_utils.py:88: error: Name 'Tensor' is not defined torch/_linalg_utils.py:88: error: Name 'Optional' is not defined torch/_linalg_utils.py:88: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Optional") torch/_linalg_utils.py:88: error: Name 'Tuple' is not defined torch/_linalg_utils.py:88: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Tuple") torch/_jit_internal.py:17: error: Need type annotation for 'boolean_dispatched' torch/_jit_internal.py:474: error: Need type annotation for '_overloaded_fns' (hint: "_overloaded_fns: Dict[<type>, <type>] = ...") torch/_jit_internal.py:512: error: Need type annotation for '_overloaded_methods' (hint: "_overloaded_methods: Dict[<type>, <type>] = ...") torch/_jit_internal.py:648: error: Incompatible types in assignment (expression has type "FinalCls", variable has type "_SpecialForm") torch/sparse/__init__.py:11: error: Name 'Tensor' is not defined torch/sparse/__init__.py:71: error: Name 'Tensor' is not defined torch/sparse/__init__.py:71: error: Name 'Optional' is not defined torch/sparse/__init__.py:71: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Optional") torch/sparse/__init__.py:71: error: Name 'Tuple' is not defined torch/sparse/__init__.py:71: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Tuple") torch/nn/init.py:109: error: Name 'Tensor' is not defined torch/nn/init.py:126: error: Name 'Tensor' is not defined torch/nn/init.py:142: error: Name 'Tensor' is not defined torch/nn/init.py:165: error: Name 'Tensor' is not defined torch/nn/init.py:180: error: Name 'Tensor' is not defined torch/nn/init.py:194: error: Name 'Tensor' is not defined torch/nn/init.py:287: error: Name 'Tensor' is not defined torch/nn/init.py:315: error: Name 'Tensor' is not defined torch/multiprocessing/reductions.py:8: error: No library stub file for standard library module 'multiprocessing.util' torch/multiprocessing/reductions.py:9: error: No library stub file for standard library module 'multiprocessing.reduction' torch/multiprocessing/reductions.py:17: error: No library stub file for standard library module 'multiprocessing.resource_sharer' torch/jit/_builtins.py:72: error: Module has no attribute "_no_grad_embedding_renorm_" torch/jit/_builtins.py:80: error: Module has no attribute "stft" torch/jit/_builtins.py:81: error: Module has no attribute "cdist" torch/jit/_builtins.py:82: error: Module has no attribute "norm" torch/jit/_builtins.py:83: error: Module has no attribute "nuclear_norm" torch/jit/_builtins.py:84: error: Module has no attribute "frobenius_norm" torch/backends/cudnn/__init__.py:8: error: Cannot find implementation or library stub for module named 'torch._C' torch/backends/cudnn/__init__.py:86: error: Need type annotation for '_handles' (hint: "_handles: Dict[<type>, <type>] = ...") torch/autograd/profiler.py:13: error: Name 'ContextDecorator' already defined (possibly by an import) torch/autograd/function.py:2: error: Cannot find implementation or library stub for module named 'torch._C' torch/autograd/function.py:2: note: See https://mypy.readthedocs.io/en/latest/running_mypy.html#missing-imports torch/autograd/function.py:109: error: Unsupported dynamic base class "with_metaclass" torch/serialization.py:609: error: "Callable[[Any], Any]" has no attribute "cache" torch/_lowrank.py:11: error: Name 'Tensor' is not defined torch/_lowrank.py:13: error: Name 'Optional' is not defined torch/_lowrank.py:13: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Optional") torch/_lowrank.py:14: error: Name 'Optional' is not defined torch/_lowrank.py:14: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Optional") torch/_lowrank.py:14: error: Name 'Tensor' is not defined torch/_lowrank.py:82: error: Name 'Tensor' is not defined torch/_lowrank.py:82: error: Name 'Optional' is not defined torch/_lowrank.py:82: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Optional") torch/_lowrank.py:82: error: Name 'Tuple' is not defined torch/_lowrank.py:82: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Tuple") torch/_lowrank.py:130: error: Name 'Tensor' is not defined torch/_lowrank.py:130: error: Name 'Optional' is not defined torch/_lowrank.py:130: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Optional") torch/_lowrank.py:130: error: Name 'Tuple' is not defined torch/_lowrank.py:130: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Tuple") torch/_lowrank.py:167: error: Name 'Tensor' is not defined torch/_lowrank.py:167: error: Name 'Optional' is not defined torch/_lowrank.py:167: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Optional") torch/_lowrank.py:167: error: Name 'Tuple' is not defined torch/_lowrank.py:167: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Tuple") torch/quantization/observer.py:45: error: Variable "torch.quantization.observer.ABC" is not valid as a type torch/quantization/observer.py:45: note: See https://mypy.readthedocs.io/en/latest/common_issues.html#variables-vs-type-aliases torch/quantization/observer.py:45: error: Invalid base class "ABC" torch/quantization/observer.py:127: error: Name 'Tensor' is not defined torch/quantization/observer.py:127: error: Name 'Tuple' is not defined torch/quantization/observer.py:127: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Tuple") torch/quantization/observer.py:172: error: Module has no attribute "per_tensor_symmetric" torch/quantization/observer.py:172: error: Module has no attribute "per_channel_symmetric" torch/quantization/observer.py:192: error: Name 'Tensor' is not defined torch/quantization/observer.py:192: error: Name 'Tuple' is not defined torch/quantization/observer.py:192: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Tuple") torch/quantization/observer.py:233: error: Module has no attribute "per_tensor_symmetric" torch/quantization/observer.py:233: error: Module has no attribute "per_channel_symmetric" torch/quantization/observer.py:534: error: Name 'Tensor' is not defined torch/quantization/observer.py:885: error: Name 'Tensor' is not defined torch/quantization/observer.py:885: error: Name 'Tuple' is not defined torch/quantization/observer.py:885: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Tuple") torch/quantization/observer.py:894: error: Cannot determine type of 'max_val' torch/quantization/observer.py:894: error: Cannot determine type of 'min_val' torch/quantization/observer.py:899: error: Cannot determine type of 'min_val' torch/quantization/observer.py:902: error: Name 'Tensor' is not defined torch/quantization/observer.py:925: error: Name 'Tensor' is not defined torch/quantization/observer.py:928: error: Cannot determine type of 'min_val' torch/quantization/observer.py:929: error: Cannot determine type of 'max_val' torch/quantization/observer.py:946: error: Argument "min" to "histc" has incompatible type "Tuple[Tensor, Tensor]"; expected "Union[int, float, bool]" torch/quantization/observer.py:946: error: Argument "max" to "histc" has incompatible type "Tuple[Tensor, Tensor]"; expected "Union[int, float, bool]" torch/quantization/observer.py:1056: error: Module has no attribute "per_tensor_symmetric" torch/quantization/observer.py:1058: error: Module has no attribute "per_channel_symmetric" torch/nn/quantized/functional.py:76: error: Name 'Tensor' is not defined torch/nn/quantized/functional.py:76: error: Name 'BroadcastingList2' is not defined torch/nn/quantized/functional.py:259: error: Name 'Tensor' is not defined torch/nn/quantized/functional.py:259: error: Name 'Optional' is not defined torch/nn/quantized/functional.py:259: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Optional") torch/nn/quantized/functional.py:289: error: Module has no attribute "ops" torch/nn/quantized/functional.py:290: error: Module has no attribute "ops" torch/nn/quantized/functional.py:308: error: Name 'Tensor' is not defined torch/nn/quantized/functional.py:326: error: Name 'Tensor' is not defined torch/nn/quantized/functional.py:356: error: Name 'Tensor' is not defined torch/nn/quantized/functional.py:371: error: Name 'Tensor' is not defined torch/nn/quantized/functional.py:400: error: Name 'Tensor' is not defined torch/nn/quantized/functional.py:400: error: Name 'Optional' is not defined torch/nn/quantized/functional.py:400: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Optional") torch/nn/quantized/functional.py:430: error: Name 'Tensor' is not defined torch/nn/quantized/functional.py:448: error: Name 'Tensor' is not defined torch/nn/quantized/modules/linear.py:26: error: Module has no attribute "ops" torch/nn/quantized/modules/linear.py:28: error: Module has no attribute "ops" torch/nn/quantized/modules/functional_modules.py:40: error: Name 'Tensor' is not defined torch/nn/quantized/modules/functional_modules.py:47: error: Name 'Tensor' is not defined torch/nn/quantized/modules/functional_modules.py:54: error: Name 'Tensor' is not defined torch/nn/quantized/modules/functional_modules.py:61: error: Name 'Tensor' is not defined torch/nn/quantized/modules/functional_modules.py:68: error: Name 'List' is not defined torch/nn/quantized/modules/functional_modules.py:68: note: Did you forget to import it from "typing"? (Suggestion: "from typing import List") torch/nn/quantized/modules/functional_modules.py:68: error: Name 'Tensor' is not defined torch/nn/quantized/modules/functional_modules.py:75: error: Name 'Tensor' is not defined torch/nn/quantized/modules/functional_modules.py:140: error: Name 'Tensor' is not defined torch/nn/quantized/modules/functional_modules.py:146: error: Name 'Tensor' is not defined torch/nn/quantized/modules/functional_modules.py:151: error: Name 'Tensor' is not defined torch/nn/quantized/modules/functional_modules.py:157: error: Name 'Tensor' is not defined torch/nn/quantized/modules/functional_modules.py:162: error: Name 'List' is not defined torch/nn/quantized/modules/functional_modules.py:162: note: Did you forget to import it from "typing"? (Suggestion: "from typing import List") torch/nn/quantized/modules/functional_modules.py:162: error: Name 'Tensor' is not defined torch/nn/quantized/modules/functional_modules.py:168: error: Name 'Tensor' is not defined torch/multiprocessing/spawn.py:9: error: Module 'torch.multiprocessing' has no attribute '_prctl_pr_set_pdeathsig' torch/multiprocessing/__init__.py:28: error: Module has no attribute "__all__" torch/jit/frontend.py:9: error: Cannot find implementation or library stub for module named 'torch._C._jit_tree_views' torch/jit/annotations.py:6: error: Module 'torch._jit_internal' has no attribute 'BroadcastingList2'; maybe "BroadcastingList1" or "BroadcastingListCls"? torch/jit/annotations.py:6: error: Module 'torch._jit_internal' has no attribute 'BroadcastingList3'; maybe "BroadcastingList1" or "BroadcastingListCls"? torch/jit/annotations.py:9: error: Cannot find implementation or library stub for module named 'torch._C' torch/distributions/distribution.py:16: error: Need type annotation for 'arg_constraints' (hint: "arg_constraints: Dict[<type>, <type>] = ...") torch/distributions/distribution.py:74: error: Name 'arg_constraints' already defined on line 16 torch/distributions/distribution.py:84: error: Name 'support' already defined on line 15 torch/functional.py:114: error: Name 'Tuple' is not defined torch/functional.py:114: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Tuple") torch/functional.py:114: error: Name 'Optional' is not defined torch/functional.py:114: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Optional") torch/functional.py:189: error: Incompatible types in assignment (expression has type "None", variable has type "Tensor") torch/functional.py:200: error: Argument 1 to "_indices_product" has incompatible type "Tuple[int, ...]"; expected "List[int]" torch/functional.py:204: error: No overload variant of "__setitem__" of "list" matches argument types "Tensor", "int" torch/functional.py:204: note: Possible overload variants: torch/functional.py:204: note: def __setitem__(self, int, int) -> None torch/functional.py:204: note: def __setitem__(self, slice, Iterable[int]) -> None torch/functional.py:204: error: No overload variant of "__getitem__" of "list" matches argument type "Tensor" torch/functional.py:204: note: def __getitem__(self, int) -> int torch/functional.py:204: note: def __getitem__(self, slice) -> List[int] torch/functional.py:207: error: "Tensor" has no attribute "copy_" torch/functional.py:212: error: No overload variant of "__setitem__" of "list" matches argument types "Tensor", "int" torch/functional.py:212: note: Possible overload variants: torch/functional.py:212: note: def __setitem__(self, int, int) -> None torch/functional.py:212: note: def __setitem__(self, slice, Iterable[int]) -> None torch/functional.py:212: error: No overload variant of "__getitem__" of "list" matches argument type "Tensor" torch/functional.py:212: note: def __getitem__(self, int) -> int torch/functional.py:212: note: def __getitem__(self, slice) -> List[int] torch/functional.py:215: error: Incompatible types in assignment (expression has type "None", variable has type "Tensor") torch/functional.py:334: error: Name 'Optional' is not defined torch/functional.py:334: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Optional") torch/functional.py:429: error: Argument 2 to "pad" has incompatible type "Tuple[int, int]"; expected "List[int]" torch/functional.py:431: error: Module has no attribute "stft" torch/functional.py:766: error: Module has no attribute "cdist" torch/functional.py:768: error: Module has no attribute "cdist" torch/functional.py:770: error: Module has no attribute "cdist" torch/functional.py:775: error: Name 'Optional' is not defined torch/functional.py:775: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Optional") torch/functional.py:780: error: Name 'Optional' is not defined torch/functional.py:780: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Optional") torch/functional.py:780: error: Name 'number' is not defined torch/functional.py:780: error: Name 'norm' already defined on line 775 torch/functional.py:785: error: Name 'Optional' is not defined torch/functional.py:785: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Optional") torch/functional.py:785: error: Name 'number' is not defined torch/functional.py:785: error: Name 'norm' already defined on line 775 torch/functional.py:790: error: Name 'Optional' is not defined torch/functional.py:790: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Optional") torch/functional.py:790: error: Name 'norm' already defined on line 775 torch/functional.py:795: error: Name 'norm' already defined on line 775 torch/functional.py:960: error: Name 'Any' is not defined torch/functional.py:960: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Any") torch/functional.py:960: error: Name 'Tuple' is not defined torch/functional.py:960: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Tuple") torch/functional.py:1036: error: Argument 1 to "len" has incompatible type "int"; expected "Sized" torch/functional.py:1041: error: Name 'Optional' is not defined torch/functional.py:1041: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Optional") torch/functional.py:1041: error: Name 'Tuple' is not defined torch/functional.py:1041: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Tuple") torch/functional.py:1056: error: Name 'Optional' is not defined torch/functional.py:1056: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Optional") torch/functional.py:1056: error: Name 'Tuple' is not defined torch/functional.py:1056: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Tuple") torch/distributions/von_mises.py:87: error: Incompatible types in assignment (expression has type "_Real", base class "Distribution" defined the type as "None") torch/distributions/negative_binomial.py:25: error: Incompatible types in assignment (expression has type "_IntegerGreaterThan", base class "Distribution" defined the type as "None") torch/distributions/multivariate_normal.py:116: error: Incompatible types in assignment (expression has type "_Real", base class "Distribution" defined the type as "None") torch/distributions/laplace.py:23: error: Incompatible types in assignment (expression has type "_Real", base class "Distribution" defined the type as "None") torch/distributions/independent.py:34: error: Need type annotation for 'arg_constraints' (hint: "arg_constraints: Dict[<type>, <type>] = ...") torch/distributions/cauchy.py:28: error: Incompatible types in assignment (expression has type "_Real", base class "Distribution" defined the type as "None") torch/distributions/poisson.py:28: error: Incompatible types in assignment (expression has type "_IntegerGreaterThan", base class "Distribution" defined the type as "None") torch/distributions/one_hot_categorical.py:32: error: Incompatible types in assignment (expression has type "_Simplex", base class "Distribution" defined the type as "None") torch/distributions/normal.py:27: error: Incompatible types in assignment (expression has type "_Real", base class "Distribution" defined the type as "None") torch/distributions/lowrank_multivariate_normal.py:79: error: Incompatible types in assignment (expression has type "_Real", base class "Distribution" defined the type as "None") torch/distributions/gamma.py:30: error: Incompatible types in assignment (expression has type "_GreaterThan", base class "Distribution" defined the type as "None") torch/distributions/exponential.py:23: error: Incompatible types in assignment (expression has type "_GreaterThan", base class "Distribution" defined the type as "None") torch/distributions/fishersnedecor.py:25: error: Incompatible types in assignment (expression has type "_GreaterThan", base class "Distribution" defined the type as "None") torch/distributions/dirichlet.py:44: error: Incompatible types in assignment (expression has type "_Simplex", base class "Distribution" defined the type as "None") torch/nn/quantized/dynamic/modules/rnn.py:230: error: Incompatible types in assignment (expression has type "int", variable has type "Tensor") torch/nn/quantized/dynamic/modules/rnn.py:232: error: Incompatible types in assignment (expression has type "int", variable has type "Tensor") torch/nn/quantized/dynamic/modules/rnn.py:236: error: Incompatible return value type (got "Tuple[Any, Tensor, Any]", expected "Tuple[int, int, int]") torch/nn/quantized/dynamic/modules/rnn.py:351: error: Incompatible types in assignment (expression has type "Type[LSTM]", base class "RNNBase" defined the type as "Type[RNNBase]") torch/nn/quantized/dynamic/modules/rnn.py:381: error: Module has no attribute "quantized_lstm" torch/nn/quantized/dynamic/modules/rnn.py:385: error: Module has no attribute "quantized_lstm" torch/nn/quantized/dynamic/modules/rnn.py:414: error: Argument 1 to "forward_impl" of "LSTM" has incompatible type "PackedSequence"; expected "Tensor" torch/nn/quantized/dynamic/modules/rnn.py:416: error: Incompatible types in assignment (expression has type "PackedSequence", variable has type "Tensor") torch/nn/quantized/dynamic/modules/rnn.py:418: error: Incompatible return value type (got "Tuple[Tensor, Tuple[Tensor, Tensor]]", expected "Tuple[PackedSequence, Tuple[Tensor, Tensor]]") torch/nn/quantized/dynamic/modules/rnn.py:420: error: Argument 1 of "permute_hidden" is incompatible with supertype "RNNBase"; supertype defines the argument type as "Tensor" torch/nn/quantized/dynamic/modules/rnn.py:420: error: Return type "Tuple[Tensor, Tensor]" of "permute_hidden" incompatible with return type "Tensor" in supertype "RNNBase" torch/nn/quantized/dynamic/modules/rnn.py:426: error: Argument 2 of "check_forward_args" is incompatible with supertype "RNNBase"; supertype defines the argument type as "Tensor" torch/nn/intrinsic/qat/modules/conv_fused.py:232: error: Incompatible types in assignment (expression has type "Type[ConvBnReLU2d]", base class "ConvBn2d" defined the type as "Type[ConvBn2d]") torch/distributions/beta.py:27: error: Incompatible types in assignment (expression has type "_Interval", base class "Distribution" defined the type as "None") torch/distributions/geometric.py:31: error: Incompatible types in assignment (expression has type "_IntegerGreaterThan", base class "Distribution" defined the type as "None") torch/distributions/continuous_bernoulli.py:38: error: Incompatible types in assignment (expression has type "_Interval", base class "Distribution" defined the type as "None") torch/distributions/bernoulli.py:30: error: Incompatible types in assignment (expression has type "_Boolean", base class "Distribution" defined the type as "None") torch/quantization/fake_quantize.py:126: error: Module has no attribute "per_tensor_symmetric" torch/quantization/fake_quantize.py:132: error: Module has no attribute "per_channel_symmetric" torch/distributions/transformed_distribution.py:41: error: Need type annotation for 'arg_constraints' (hint: "arg_constraints: Dict[<type>, <type>] = ...") torch/jit/__init__.py:1: error: Cannot find implementation or library stub for module named 'torch._C' torch/jit/__init__.py:15: error: Module 'torch.utils' has no attribute 'set_module' torch/jit/__init__.py:70: error: Name 'Attribute' already defined on line 68 torch/jit/__init__.py:213: error: On Python 3 '{}'.format(b'abc') produces "b'abc'"; use !r if this is a desired behavior torch/jit/__init__.py:215: error: On Python 3 '{}'.format(b'abc') produces "b'abc'"; use !r if this is a desired behavior torch/jit/__init__.py:1524: error: Unsupported dynamic base class "with_metaclass" torch/jit/__init__.py:1869: error: Name 'ScriptModule' already defined on line 1524 torch/jit/__init__.py:1998: error: Need type annotation for '_jit_caching_layer' torch/jit/__init__.py:1999: error: Need type annotation for '_jit_function_overload_caching' torch/distributions/relaxed_categorical.py:34: error: Incompatible types in assignment (expression has type "_Real", base class "Distribution" defined the type as "None") torch/distributions/relaxed_categorical.py:108: error: Incompatible types in assignment (expression has type "_Simplex", base class "Distribution" defined the type as "None") torch/distributions/relaxed_bernoulli.py:31: error: Incompatible types in assignment (expression has type "_Real", base class "Distribution" defined the type as "None") torch/distributions/relaxed_bernoulli.py:114: error: Incompatible types in assignment (expression has type "_Interval", base class "Distribution" defined the type as "None") torch/distributions/logistic_normal.py:31: error: Incompatible types in assignment (expression has type "_Simplex", base class "Distribution" defined the type as "None") torch/distributions/log_normal.py:26: error: Incompatible types in assignment (expression has type "_GreaterThan", base class "Distribution" defined the type as "None") torch/distributions/half_normal.py:27: error: Incompatible types in assignment (expression has type "_GreaterThan", base class "Distribution" defined the type as "None") torch/distributions/half_cauchy.py:28: error: Incompatible types in assignment (expression has type "_GreaterThan", base class "Distribution" defined the type as "None") torch/distributions/gumbel.py:28: error: Incompatible types in assignment (expression has type "_Real", base class "Distribution" defined the type as "None") torch/nn/quantized/modules/conv.py:18: error: Module 'torch.nn.utils' has no attribute 'fuse_conv_bn_weights' torch/nn/quantized/modules/conv.py:209: error: Name 'Optional' is not defined torch/nn/quantized/modules/conv.py:209: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Optional") torch/nn/quantized/modules/conv.py:214: error: Module has no attribute "ops" torch/nn/quantized/modules/conv.py:321: error: Name 'Optional' is not defined torch/nn/quantized/modules/conv.py:321: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Optional") torch/nn/quantized/modules/conv.py:323: error: Module has no attribute "ops" torch/nn/quantized/modules/conv.py:447: error: Name 'Optional' is not defined torch/nn/quantized/modules/conv.py:447: note: Did you forget to import it from "typing"? (Suggestion: "from typing import Optional") torch/nn/quantized/modules/conv.py:449: error: Module has no attribute "ops" torch/nn/quantized/modules/conv.py:513: error: Name 'nn.modules.conv._ConvTransposeNd' is not defined torch/nn/quantized/modules/conv.py:525: error: Name 'List' is not defined torch/nn/quantized/modules/conv.py:525: note: Did you forget to import it from "typing"? (Suggestion: "from typing import List") torch/nn/quantized/modules/conv.py:527: error: Name 'List' is not defined torch/nn/quantized/modules/conv.py:527: note: Did you forget to import it from "typing"? (Suggestion: "from typing import List") torch/nn/intrinsic/quantized/modules/conv_relu.py:8: error: Module 'torch.nn.utils' has no attribute 'fuse_conv_bn_weights' torch/nn/intrinsic/quantized/modules/conv_relu.py:21: error: Incompatible types in assignment (expression has type "Type[ConvReLU2d]", base class "Conv2d" defined the type as "Type[Conv2d]") torch/nn/intrinsic/quantized/modules/conv_relu.py:62: error: Incompatible types in assignment (expression has type "Type[ConvReLU3d]", base class "Conv3d" defined the type as "Type[Conv3d]") torch/distributions/weibull.py:25: error: Incompatible types in assignment (expression has type "_GreaterThan", base class "Distribution" defined the type as "None") torch/distributions/kl.py:35: error: Need type annotation for '_KL_MEMOIZE' (hint: "_KL_MEMOIZE: Dict[<type>, <type>] = ...") torch/distributions/studentT.py:27: error: Incompatible types in assignment (expression has type "_Real", base class "Distribution" defined the type as "None") torch/distributions/mixture_same_family.py:48: error: Need type annotation for 'arg_constraints' (hint: "arg_constraints: Dict[<type>, <type>] = ...") torch/distributions/__init__.py:158: error: Name 'transforms' is not defined torch/onnx/utils.py:21: error: Cannot find implementation or library stub for module named 'torch._C' torch/distributed/rendezvous.py:4: error: Cannot find implementation or library stub for module named 'urlparse' torch/distributed/rendezvous.py:4: error: Name 'urlparse' already defined (possibly by an import) torch/distributed/rendezvous.py:4: error: Name 'urlunparse' already defined (possibly by an import) torch/distributed/rendezvous.py:9: error: Module 'torch.distributed' has no attribute 'FileStore' torch/distributed/rendezvous.py:9: error: Module 'torch.distributed' has no attribute 'TCPStore' torch/distributed/rendezvous.py:65: error: On Python 3 '{}'.format(b'abc') produces "b'abc'"; use !r if this is a desired behavior torch/distributed/distributed_c10d.py:11: error: Module 'torch.distributed' has no attribute 'AllreduceOptions'; maybe "ReduceOptions" or "AllreduceCoalescedOptions"? torch/distributed/distributed_c10d.py:11: error: Module 'torch.distributed' has no attribute 'AllreduceCoalescedOptions'; maybe "AllreduceOptions"? torch/distributed/distributed_c10d.py:11: error: Module 'torch.distributed' has no attribute 'AllToAllOptions' torch/distributed/distributed_c10d.py:11: error: Module 'torch.distributed' has no attribute 'BroadcastOptions' torch/distributed/distributed_c10d.py:11: error: Module 'torch.distributed' has no attribute 'GatherOptions'; maybe "ScatterOptions"? torch/distributed/distributed_c10d.py:11: error: Module 'torch.distributed' has no attribute 'ReduceOptions'; maybe "AllreduceOptions", "ReduceScatterOptions", or "ReduceOp"? torch/distributed/distributed_c10d.py:11: error: Module 'torch.distributed' has no attribute 'ReduceScatterOptions'; maybe "ScatterOptions" or "ReduceOptions"? torch/distributed/distributed_c10d.py:11: error: Module 'torch.distributed' has no attribute 'ScatterOptions'; maybe "ReduceScatterOptions" or Pull Request resolved: https://github.com/pytorch/pytorch/pull/36584 Reviewed By: seemethere, ailzhang Differential Revision: D21155985 Pulled By: ezyang fbshipit-source-id: f628d4293992576207167e7c417998fad15898d1 |
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|
David Reiss
|
e75fb4356b |
Remove (most) Python 2 support from Python code (#35615)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/35615 Python 2 has reached end-of-life and is no longer supported by PyTorch. Now we can clean up a lot of cruft that we put in place to support it. These changes were all done manually, and I skipped anything that seemed like it would take more than a few seconds, so I think it makes sense to review it manually as well (though using side-by-side view and ignoring whitespace change might be helpful). Test Plan: CI Differential Revision: D20842886 Pulled By: dreiss fbshipit-source-id: 8cad4e87c45895e7ce3938a88e61157a79504aed |
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|
Amy Yang
|
37479ddf4e |
[caffe2] create and register child ws in pybind (#36741)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/36741 Create child workspace that shares parent workspace's blobs. Register child workspace in registrar to enable switching into child workspace and feeding to child workspace alone. Test Plan: numeric suite unit tests in stacked diff Reviewed By: hx89 Differential Revision: D21055567 fbshipit-source-id: 374b12aef75a4c58452c271f8961ee156ce6c559 |
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Nikita Shulga
|
527cf877d6 |
Delete old mkl_speed_test.py
Summary: It was always skipped for last 1.5 years (since D10372230 was landed) Test Plan: CI Reviewed By: ailzhang Differential Revision: D21036194 fbshipit-source-id: 9ace60b45a123a9372a88310b91f33a69ae8880c |
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Yuxi Hu
|
cf27d07e04 |
Implementation of STORM optimizer caffe2 python wrapper (#36399)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/36399 Added caffe2 python wrapper and unit test for the STORM C++ operator. Test Plan: All newly added unit tests passed using "buck test //caffe2/caffe2/python:optimizer_test -- TestStorm" {F233644598} Reviewed By: chocjy Differential Revision: D18841013 fbshipit-source-id: f692bc18412839db140202ec9a971e556db0e54f |
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Yuxi Hu
|
f7c9faab05 |
Implementation and operator test for STORM optimizer (#36225)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/36225 Implemented the [STORM](https://arxiv.org/abs/1905.10018) optimizer operator for dense and sparse cases. Test Plan: All newly added unit tests passed using "buck test //caffe2/caffe2/python/operator_test:storm_test". {F233643713} Reviewed By: chocjy Differential Revision: D18702897 fbshipit-source-id: d25eeb492aa2a03c69754d3f076a8239230b3bf4 |
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Xing Wang
|
4b3e3d8227 |
[improve logging] add the param information when logging the optimizer engine (#36558)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/36558 In the log, frequently see a large trunk of Using engine xx for rowWise Adagrad, but without information on which parameter is applied. Test Plan: Should be covered by existing testing that use optimizer Reviewed By: chocjy Differential Revision: D20985176 fbshipit-source-id: 6eb4e19e5307db53fc89b38594a3f303f1492a1c |
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Hao Lu
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fb70b4fb93 |
[caffe2] Add support for std::shared_ptr<std::vector<TensorList>> in PackRecordsOp and UnPackRecordsOp (#36550)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/36550 Separate dataset_ops changes into a separate diff. Test Plan: ``` buck test caffe2/caffe2/python/operator_test:dataset_ops_test ``` AI/AF canary (tested with D20959214): https://our.intern.facebook.com/intern/experiment_store/experiment/3298538636995/#commit1-commit2 https://our.intern.facebook.com/intern/experiment_store/experiment/2199027015376/#commit1-commit2 Reviewed By: yinghai Differential Revision: D20988910 fbshipit-source-id: b37a7bfd131813e9472a5e2fa24d681d1ef19018 |