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Add a lot of dimname overloads (#26636)
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/26636 This PR defines a lot of dimname overloads so that when named tensor support is added for those operators, we will not have to modify the autogenerated TensorMethods.h, thereby avoiding potential merge conflicts in the future. Overloads were added for the following: - all - any - argmax - argmin - cumsum - cumprod - index_copy - kthvalue - mode - permute - squeeze - index_add - index_fill - scatter - scatter_add - index_select - gather - sort - argsort Test Plan: - [namedtensor ci] Differential Revision: D17522984 Pulled By: zou3519 fbshipit-source-id: eca6dea819ba4e4e43b71b700d5cf09176f00061
This commit is contained in:
Richard Zou
Facebook Github Bot
parent
67bde6b724
commit
925e51ea7f
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@ -32,6 +32,14 @@ CAFFE2_API std::vector<int64_t> dimnames_to_positions(const Tensor& tensor, Dimn
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CAFFE2_API std::vector<Dimname>
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unify_from_right(DimnameList names, DimnameList other, const char* action = "broadcast");
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[[noreturn]] inline void reportNYIDimnameOverload(const char* op_name) {
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TORCH_CHECK(
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false,
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op_name, ": You passed a dimname (string) to this op in place of a dimension "
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"index but it does not yet support this behavior. Please pass a dimension "
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"index to work around this.");
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}
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namespace namedinference {
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// Names get propagated via the following rules:
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@ -784,7 +784,19 @@ bool aten_op_is_not_moved_to_c10_yet(const c10::OperatorName& opName) {
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{"aten::addmv", "out"},
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{"aten::addr", "out"},
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{"aten::all", "out"},
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#ifdef BUILD_NAMEDTENSOR
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{"aten::all", "dimname"},
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#endif
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#ifdef BUILD_NAMEDTENSOR
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{"aten::all", "dimname_out"},
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#endif
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{"aten::any", "out"},
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#ifdef BUILD_NAMEDTENSOR
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{"aten::any", "dimname"},
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#endif
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#ifdef BUILD_NAMEDTENSOR
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{"aten::any", "dimname_out"},
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#endif
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{"aten::arange", ""},
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{"aten::arange", "start"},
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{"aten::arange", "start_step"},
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@ -845,8 +857,20 @@ bool aten_op_is_not_moved_to_c10_yet(const c10::OperatorName& opName) {
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{"aten::cudnn_convolution_transpose", ""},
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{"aten::cumsum", ""},
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{"aten::cumsum", "out"},
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#ifdef BUILD_NAMEDTENSOR
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{"aten::cumsum", "dimname"},
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#endif
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#ifdef BUILD_NAMEDTENSOR
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{"aten::cumsum", "dimname_out"},
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#endif
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{"aten::cumprod", ""},
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{"aten::cumprod", "out"},
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#ifdef BUILD_NAMEDTENSOR
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{"aten::cumprod", "dimname"},
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#endif
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#ifdef BUILD_NAMEDTENSOR
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{"aten::cumprod", "dimname_out"},
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#endif
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{"aten::div", "out"},
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{"aten::dot", "out"},
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{"aten::embedding_bag", ""},
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@ -902,12 +926,24 @@ bool aten_op_is_not_moved_to_c10_yet(const c10::OperatorName& opName) {
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{"aten::_cufft_set_plan_cache_max_size", ""},
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{"aten::_cufft_clear_plan_cache", ""},
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{"aten::index", "Tensor"},
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#ifdef BUILD_NAMEDTENSOR
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{"aten::index_copy_", "dimname"},
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#endif
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#ifdef BUILD_NAMEDTENSOR
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{"aten::index_copy", "dimname"},
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#endif
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{"aten::index_put_", ""},
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{"aten::index_put", ""},
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{"aten::_index_put_impl_", ""},
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{"aten::instance_norm", ""},
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{"aten::inverse", "out"},
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{"aten::kthvalue", "values"},
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#ifdef BUILD_NAMEDTENSOR
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{"aten::kthvalue", "dimname"},
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#endif
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#ifdef BUILD_NAMEDTENSOR
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{"aten::kthvalue", "dimname_out"},
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#endif
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{"aten::layer_norm", ""},
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{"aten::native_layer_norm", ""},
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{"aten::native_layer_norm_backward", ""},
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@ -980,6 +1016,12 @@ bool aten_op_is_not_moved_to_c10_yet(const c10::OperatorName& opName) {
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{"aten::miopen_rnn_backward", ""},
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{"aten::mm", "out"},
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{"aten::mode", "values"},
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#ifdef BUILD_NAMEDTENSOR
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{"aten::mode", "dimname"},
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#endif
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#ifdef BUILD_NAMEDTENSOR
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{"aten::mode", "dimname_out"},
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#endif
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{"aten::mul", "out"},
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{"aten::mv", "out"},
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{"aten::native_batch_norm", ""},
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@ -1055,6 +1097,12 @@ bool aten_op_is_not_moved_to_c10_yet(const c10::OperatorName& opName) {
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{"aten::softmax", ""},
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#ifdef BUILD_NAMEDTENSOR
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{"aten::softmax", ""},
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#endif
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#ifdef BUILD_NAMEDTENSOR
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{"aten::squeeze", "dimname"},
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#endif
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#ifdef BUILD_NAMEDTENSOR
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{"aten::squeeze_", "dimname"},
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#endif
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{"aten::sspaddmm", "out"},
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{"aten::stack", "out"},
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@ -1169,6 +1217,24 @@ bool aten_op_is_not_moved_to_c10_yet(const c10::OperatorName& opName) {
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{"aten::set_", "source_Storage"},
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{"aten::set_", "source_Storage_storage_offset"},
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{"aten::set_quantizer_", ""},
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#ifdef BUILD_NAMEDTENSOR
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{"aten::index_add", "dimname"},
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#endif
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#ifdef BUILD_NAMEDTENSOR
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{"aten::index_fill", "dimname_Scalar"},
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#endif
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#ifdef BUILD_NAMEDTENSOR
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{"aten::index_fill", "dimname_Tensor"},
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#endif
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#ifdef BUILD_NAMEDTENSOR
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{"aten::scatter", "dimname_src"},
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#endif
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#ifdef BUILD_NAMEDTENSOR
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{"aten::scatter", "dimname_value"},
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#endif
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#ifdef BUILD_NAMEDTENSOR
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{"aten::scatter_add", "dimname"},
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#endif
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{"aten::addbmm", "out"},
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{"aten::random_", "from"},
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{"aten::random_", "to"},
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@ -1199,9 +1265,21 @@ bool aten_op_is_not_moved_to_c10_yet(const c10::OperatorName& opName) {
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{"aten::lt", "Tensor_out"},
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{"aten::take", "out"},
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{"aten::index_select", "out"},
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#ifdef BUILD_NAMEDTENSOR
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{"aten::index_select", "dimname_out"},
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#endif
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#ifdef BUILD_NAMEDTENSOR
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{"aten::index_select", "dimname"},
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#endif
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{"aten::masked_select", "out"},
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{"aten::nonzero", "out"},
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{"aten::gather", "out"},
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#ifdef BUILD_NAMEDTENSOR
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{"aten::gather", "dimname_out"},
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#endif
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#ifdef BUILD_NAMEDTENSOR
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{"aten::gather", "dimname"},
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#endif
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{"aten::addcmul", "out"},
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{"aten::addcdiv", "out"},
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{"aten::lstsq", "X"},
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@ -1237,6 +1315,15 @@ bool aten_op_is_not_moved_to_c10_yet(const c10::OperatorName& opName) {
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{"aten::min", "out"},
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{"aten::max", "out"},
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{"aten::sort", "values"},
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#ifdef BUILD_NAMEDTENSOR
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{"aten::sort", "dimname_values"},
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#endif
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#ifdef BUILD_NAMEDTENSOR
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{"aten::sort", "dimname"},
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#endif
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#ifdef BUILD_NAMEDTENSOR
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{"aten::argsort", "dimname"},
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#endif
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{"aten::topk", "values"},
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{"aten::renorm", "out"},
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{"aten::pow", "Tensor_Tensor_out"},
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@ -438,8 +438,14 @@ class CAFFE2_API Tensor {
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Tensor addr(const Tensor & vec1, const Tensor & vec2, Scalar beta=1, Scalar alpha=1) const;
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Tensor & addr_(const Tensor & vec1, const Tensor & vec2, Scalar beta=1, Scalar alpha=1) const;
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Tensor all(int64_t dim, bool keepdim=false) const;
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#ifdef BUILD_NAMEDTENSOR
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Tensor all(Dimname dim, bool keepdim=false) const;
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#endif
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bool allclose(const Tensor & other, double rtol=1e-05, double atol=1e-08, bool equal_nan=false) const;
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Tensor any(int64_t dim, bool keepdim=false) const;
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#ifdef BUILD_NAMEDTENSOR
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Tensor any(Dimname dim, bool keepdim=false) const;
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#endif
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Tensor argmax(c10::optional<int64_t> dim=c10::nullopt, bool keepdim=false) const;
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Tensor argmin(c10::optional<int64_t> dim=c10::nullopt, bool keepdim=false) const;
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Tensor as_strided(IntArrayRef size, IntArrayRef stride, c10::optional<int64_t> storage_offset=c10::nullopt) const;
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@ -478,7 +484,13 @@ class CAFFE2_API Tensor {
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Tensor cosh() const;
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Tensor & cosh_() const;
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Tensor cumsum(int64_t dim, c10::optional<ScalarType> dtype=c10::nullopt) const;
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#ifdef BUILD_NAMEDTENSOR
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Tensor cumsum(Dimname dim, c10::optional<ScalarType> dtype=c10::nullopt) const;
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#endif
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Tensor cumprod(int64_t dim, c10::optional<ScalarType> dtype=c10::nullopt) const;
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#ifdef BUILD_NAMEDTENSOR
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Tensor cumprod(Dimname dim, c10::optional<ScalarType> dtype=c10::nullopt) const;
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#endif
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Tensor det() const;
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Tensor diag_embed(int64_t offset=0, int64_t dim1=-2, int64_t dim2=-1) const;
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Tensor diagflat(int64_t offset=0) const;
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@ -526,6 +538,12 @@ class CAFFE2_API Tensor {
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Tensor index(TensorList indices) const;
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Tensor & index_copy_(int64_t dim, const Tensor & index, const Tensor & source) const;
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Tensor index_copy(int64_t dim, const Tensor & index, const Tensor & source) const;
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#ifdef BUILD_NAMEDTENSOR
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Tensor & index_copy_(Dimname dim, const Tensor & index, const Tensor & source) const;
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#endif
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#ifdef BUILD_NAMEDTENSOR
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Tensor index_copy(Dimname dim, const Tensor & index, const Tensor & source) const;
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#endif
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Tensor & index_put_(TensorList indices, const Tensor & values, bool accumulate=false) const;
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Tensor index_put(TensorList indices, const Tensor & values, bool accumulate=false) const;
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Tensor inverse() const;
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@ -537,6 +555,9 @@ class CAFFE2_API Tensor {
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bool is_same_size(const Tensor & other) const;
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bool is_signed() const;
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std::tuple<Tensor,Tensor> kthvalue(int64_t k, int64_t dim=-1, bool keepdim=false) const;
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#ifdef BUILD_NAMEDTENSOR
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std::tuple<Tensor,Tensor> kthvalue(int64_t k, Dimname dim, bool keepdim=false) const;
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#endif
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Tensor log() const;
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Tensor & log_() const;
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Tensor log10() const;
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@ -583,6 +604,9 @@ class CAFFE2_API Tensor {
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#endif
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Tensor mm(const Tensor & mat2) const;
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std::tuple<Tensor,Tensor> mode(int64_t dim=-1, bool keepdim=false) const;
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#ifdef BUILD_NAMEDTENSOR
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std::tuple<Tensor,Tensor> mode(Dimname dim, bool keepdim=false) const;
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#endif
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Tensor mul(const Tensor & other) const;
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Tensor & mul_(const Tensor & other) const;
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Tensor mul(Scalar other) const;
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@ -643,8 +667,14 @@ class CAFFE2_API Tensor {
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std::vector<Tensor> split_with_sizes(IntArrayRef split_sizes, int64_t dim=0) const;
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Tensor squeeze() const;
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Tensor squeeze(int64_t dim) const;
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#ifdef BUILD_NAMEDTENSOR
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Tensor squeeze(Dimname dim) const;
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#endif
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Tensor & squeeze_() const;
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Tensor & squeeze_(int64_t dim) const;
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#ifdef BUILD_NAMEDTENSOR
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Tensor & squeeze_(Dimname dim) const;
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#endif
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Tensor sspaddmm(const Tensor & mat1, const Tensor & mat2, Scalar beta=1, Scalar alpha=1) const;
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Tensor stft(int64_t n_fft, c10::optional<int64_t> hop_length=c10::nullopt, c10::optional<int64_t> win_length=c10::nullopt, const Tensor & window={}, bool normalized=false, bool onesided=true) const;
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int64_t stride(int64_t dim) const;
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@ -768,16 +798,34 @@ class CAFFE2_API Tensor {
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Tensor & put_(const Tensor & index, const Tensor & source, bool accumulate=false) const;
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Tensor & index_add_(int64_t dim, const Tensor & index, const Tensor & source) const;
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Tensor index_add(int64_t dim, const Tensor & index, const Tensor & source) const;
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#ifdef BUILD_NAMEDTENSOR
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Tensor index_add(Dimname dim, const Tensor & index, const Tensor & source) const;
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#endif
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Tensor & index_fill_(int64_t dim, const Tensor & index, Scalar value) const;
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Tensor index_fill(int64_t dim, const Tensor & index, Scalar value) const;
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Tensor & index_fill_(int64_t dim, const Tensor & index, const Tensor & value) const;
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Tensor index_fill(int64_t dim, const Tensor & index, const Tensor & value) const;
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#ifdef BUILD_NAMEDTENSOR
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Tensor index_fill(Dimname dim, const Tensor & index, Scalar value) const;
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#endif
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#ifdef BUILD_NAMEDTENSOR
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Tensor index_fill(Dimname dim, const Tensor & index, const Tensor & value) const;
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#endif
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Tensor & scatter_(int64_t dim, const Tensor & index, const Tensor & src) const;
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Tensor scatter(int64_t dim, const Tensor & index, const Tensor & src) const;
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Tensor & scatter_(int64_t dim, const Tensor & index, Scalar value) const;
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Tensor scatter(int64_t dim, const Tensor & index, Scalar value) const;
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#ifdef BUILD_NAMEDTENSOR
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Tensor scatter(Dimname dim, const Tensor & index, const Tensor & src) const;
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#endif
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#ifdef BUILD_NAMEDTENSOR
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Tensor scatter(Dimname dim, const Tensor & index, Scalar value) const;
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#endif
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Tensor & scatter_add_(int64_t dim, const Tensor & index, const Tensor & src) const;
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Tensor scatter_add(int64_t dim, const Tensor & index, const Tensor & src) const;
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#ifdef BUILD_NAMEDTENSOR
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Tensor scatter_add(Dimname dim, const Tensor & index, const Tensor & src) const;
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#endif
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Tensor & lt_(Scalar other) const;
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Tensor & lt_(const Tensor & other) const;
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Tensor & gt_(Scalar other) const;
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@ -856,10 +904,16 @@ class CAFFE2_API Tensor {
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Tensor lt(const Tensor & other) const;
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Tensor take(const Tensor & index) const;
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Tensor index_select(int64_t dim, const Tensor & index) const;
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#ifdef BUILD_NAMEDTENSOR
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Tensor index_select(Dimname dim, const Tensor & index) const;
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#endif
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Tensor masked_select(const Tensor & mask) const;
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Tensor nonzero() const;
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std::vector<Tensor> nonzero_numpy() const;
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Tensor gather(int64_t dim, const Tensor & index, bool sparse_grad=false) const;
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#ifdef BUILD_NAMEDTENSOR
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Tensor gather(Dimname dim, const Tensor & index, bool sparse_grad=false) const;
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#endif
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Tensor addcmul(const Tensor & tensor1, const Tensor & tensor2, Scalar value=1) const;
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Tensor & addcmul_(const Tensor & tensor1, const Tensor & tensor2, Scalar value=1) const;
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Tensor addcdiv(const Tensor & tensor1, const Tensor & tensor2, Scalar value=1) const;
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@ -900,7 +954,13 @@ class CAFFE2_API Tensor {
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Tensor max() const;
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Tensor median() const;
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std::tuple<Tensor,Tensor> sort(int64_t dim=-1, bool descending=false) const;
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#ifdef BUILD_NAMEDTENSOR
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std::tuple<Tensor,Tensor> sort(Dimname dim, bool descending=false) const;
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#endif
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Tensor argsort(int64_t dim=-1, bool descending=false) const;
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#ifdef BUILD_NAMEDTENSOR
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Tensor argsort(Dimname dim, bool descending=false) const;
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#endif
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std::tuple<Tensor,Tensor> topk(int64_t k, int64_t dim=-1, bool largest=true, bool sorted=true) const;
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Tensor all() const;
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Tensor any() const;
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@ -361,6 +361,16 @@ inline Tensor Tensor::all(int64_t dim, bool keepdim) const {
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op, impl::dispatchTypeId(at::detail::multi_dispatch_tensor_type_set(*this)), const_cast<Tensor&>(*this), dim, keepdim);
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#endif
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}
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#ifdef BUILD_NAMEDTENSOR
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inline Tensor Tensor::all(Dimname dim, bool keepdim) const {
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#ifdef USE_STATIC_DISPATCH
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return TypeDefault::all(const_cast<Tensor&>(*this), dim, keepdim);
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#else
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static auto table = globalATenDispatch().getOpTable("aten::all.dimname(Tensor self, Dimname dim, bool keepdim=False) -> Tensor");
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return table->getOp<Tensor (const Tensor &, Dimname, bool)>(at::detail::multi_dispatch_tensor_type_set(*this))(const_cast<Tensor&>(*this), dim, keepdim);
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#endif
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}
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#endif
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inline bool Tensor::allclose(const Tensor & other, double rtol, double atol, bool equal_nan) const {
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#ifdef USE_STATIC_DISPATCH
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return TypeDefault::allclose(const_cast<Tensor&>(*this), other, rtol, atol, equal_nan);
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@ -379,6 +389,16 @@ inline Tensor Tensor::any(int64_t dim, bool keepdim) const {
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op, impl::dispatchTypeId(at::detail::multi_dispatch_tensor_type_set(*this)), const_cast<Tensor&>(*this), dim, keepdim);
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#endif
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}
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#ifdef BUILD_NAMEDTENSOR
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inline Tensor Tensor::any(Dimname dim, bool keepdim) const {
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#ifdef USE_STATIC_DISPATCH
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return TypeDefault::any(const_cast<Tensor&>(*this), dim, keepdim);
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#else
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static auto table = globalATenDispatch().getOpTable("aten::any.dimname(Tensor self, Dimname dim, bool keepdim=False) -> Tensor");
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return table->getOp<Tensor (const Tensor &, Dimname, bool)>(at::detail::multi_dispatch_tensor_type_set(*this))(const_cast<Tensor&>(*this), dim, keepdim);
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#endif
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}
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#endif
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inline Tensor Tensor::argmax(c10::optional<int64_t> dim, bool keepdim) const {
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#ifdef USE_STATIC_DISPATCH
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return TypeDefault::argmax(const_cast<Tensor&>(*this), dim, keepdim);
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@ -801,6 +821,16 @@ inline Tensor Tensor::cumsum(int64_t dim, c10::optional<ScalarType> dtype) const
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return table->getOp<Tensor (const Tensor &, int64_t, c10::optional<ScalarType>)>(at::detail::multi_dispatch_tensor_type_set(*this))(const_cast<Tensor&>(*this), dim, dtype);
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#endif
|
||||
}
|
||||
#ifdef BUILD_NAMEDTENSOR
|
||||
inline Tensor Tensor::cumsum(Dimname dim, c10::optional<ScalarType> dtype) const {
|
||||
#ifdef USE_STATIC_DISPATCH
|
||||
return TypeDefault::cumsum(const_cast<Tensor&>(*this), dim, dtype);
|
||||
#else
|
||||
static auto table = globalATenDispatch().getOpTable("aten::cumsum.dimname(Tensor self, Dimname dim, *, ScalarType? dtype=None) -> Tensor");
|
||||
return table->getOp<Tensor (const Tensor &, Dimname, c10::optional<ScalarType>)>(at::detail::multi_dispatch_tensor_type_set(*this))(const_cast<Tensor&>(*this), dim, dtype);
|
||||
#endif
|
||||
}
|
||||
#endif
|
||||
inline Tensor Tensor::cumprod(int64_t dim, c10::optional<ScalarType> dtype) const {
|
||||
#ifdef USE_STATIC_DISPATCH
|
||||
return TypeDefault::cumprod(const_cast<Tensor&>(*this), dim, dtype);
|
||||
|
|
@ -809,6 +839,16 @@ inline Tensor Tensor::cumprod(int64_t dim, c10::optional<ScalarType> dtype) cons
|
|||
return table->getOp<Tensor (const Tensor &, int64_t, c10::optional<ScalarType>)>(at::detail::multi_dispatch_tensor_type_set(*this))(const_cast<Tensor&>(*this), dim, dtype);
|
||||
#endif
|
||||
}
|
||||
#ifdef BUILD_NAMEDTENSOR
|
||||
inline Tensor Tensor::cumprod(Dimname dim, c10::optional<ScalarType> dtype) const {
|
||||
#ifdef USE_STATIC_DISPATCH
|
||||
return TypeDefault::cumprod(const_cast<Tensor&>(*this), dim, dtype);
|
||||
#else
|
||||
static auto table = globalATenDispatch().getOpTable("aten::cumprod.dimname(Tensor self, Dimname dim, *, ScalarType? dtype=None) -> Tensor");
|
||||
return table->getOp<Tensor (const Tensor &, Dimname, c10::optional<ScalarType>)>(at::detail::multi_dispatch_tensor_type_set(*this))(const_cast<Tensor&>(*this), dim, dtype);
|
||||
#endif
|
||||
}
|
||||
#endif
|
||||
inline Tensor Tensor::det() const {
|
||||
#ifdef USE_STATIC_DISPATCH
|
||||
return TypeDefault::det(const_cast<Tensor&>(*this));
|
||||
|
|
@ -1247,6 +1287,26 @@ inline Tensor Tensor::index_copy(int64_t dim, const Tensor & index, const Tensor
|
|||
op, impl::dispatchTypeId(at::detail::multi_dispatch_tensor_type_set(*this, index, source)), const_cast<Tensor&>(*this), dim, index, source);
|
||||
#endif
|
||||
}
|
||||
#ifdef BUILD_NAMEDTENSOR
|
||||
inline Tensor & Tensor::index_copy_(Dimname dim, const Tensor & index, const Tensor & source) const {
|
||||
#ifdef USE_STATIC_DISPATCH
|
||||
return TypeDefault::index_copy_(const_cast<Tensor&>(*this), dim, index, source);
|
||||
#else
|
||||
static auto table = globalATenDispatch().getOpTable("aten::index_copy_.dimname(Tensor(a!) self, Dimname dim, Tensor index, Tensor source) -> Tensor(a!)");
|
||||
return table->getOp<Tensor & (Tensor &, Dimname, const Tensor &, const Tensor &)>(at::detail::multi_dispatch_tensor_type_set(*this, index, source))(const_cast<Tensor&>(*this), dim, index, source);
|
||||
#endif
|
||||
}
|
||||
#endif
|
||||
#ifdef BUILD_NAMEDTENSOR
|
||||
inline Tensor Tensor::index_copy(Dimname dim, const Tensor & index, const Tensor & source) const {
|
||||
#ifdef USE_STATIC_DISPATCH
|
||||
return TypeDefault::index_copy(const_cast<Tensor&>(*this), dim, index, source);
|
||||
#else
|
||||
static auto table = globalATenDispatch().getOpTable("aten::index_copy.dimname(Tensor self, Dimname dim, Tensor index, Tensor source) -> Tensor");
|
||||
return table->getOp<Tensor (const Tensor &, Dimname, const Tensor &, const Tensor &)>(at::detail::multi_dispatch_tensor_type_set(*this, index, source))(const_cast<Tensor&>(*this), dim, index, source);
|
||||
#endif
|
||||
}
|
||||
#endif
|
||||
inline Tensor & Tensor::index_put_(TensorList indices, const Tensor & values, bool accumulate) const {
|
||||
#ifdef USE_STATIC_DISPATCH
|
||||
return TypeDefault::index_put_(const_cast<Tensor&>(*this), indices, values, accumulate);
|
||||
|
|
@ -1344,6 +1404,16 @@ inline std::tuple<Tensor,Tensor> Tensor::kthvalue(int64_t k, int64_t dim, bool k
|
|||
op, impl::dispatchTypeId(at::detail::multi_dispatch_tensor_type_set(*this)), const_cast<Tensor&>(*this), k, dim, keepdim);
|
||||
#endif
|
||||
}
|
||||
#ifdef BUILD_NAMEDTENSOR
|
||||
inline std::tuple<Tensor,Tensor> Tensor::kthvalue(int64_t k, Dimname dim, bool keepdim) const {
|
||||
#ifdef USE_STATIC_DISPATCH
|
||||
return TypeDefault::kthvalue(const_cast<Tensor&>(*this), k, dim, keepdim);
|
||||
#else
|
||||
static auto table = globalATenDispatch().getOpTable("aten::kthvalue.dimname(Tensor self, int k, Dimname dim, bool keepdim=False) -> (Tensor values, Tensor indices)");
|
||||
return table->getOp<std::tuple<Tensor,Tensor> (const Tensor &, int64_t, Dimname, bool)>(at::detail::multi_dispatch_tensor_type_set(*this))(const_cast<Tensor&>(*this), k, dim, keepdim);
|
||||
#endif
|
||||
}
|
||||
#endif
|
||||
inline Tensor Tensor::log() const {
|
||||
#ifdef USE_STATIC_DISPATCH
|
||||
return TypeDefault::log(const_cast<Tensor&>(*this));
|
||||
|
|
@ -1679,6 +1749,16 @@ inline std::tuple<Tensor,Tensor> Tensor::mode(int64_t dim, bool keepdim) const {
|
|||
op, impl::dispatchTypeId(at::detail::multi_dispatch_tensor_type_set(*this)), const_cast<Tensor&>(*this), dim, keepdim);
|
||||
#endif
|
||||
}
|
||||
#ifdef BUILD_NAMEDTENSOR
|
||||
inline std::tuple<Tensor,Tensor> Tensor::mode(Dimname dim, bool keepdim) const {
|
||||
#ifdef USE_STATIC_DISPATCH
|
||||
return TypeDefault::mode(const_cast<Tensor&>(*this), dim, keepdim);
|
||||
#else
|
||||
static auto table = globalATenDispatch().getOpTable("aten::mode.dimname(Tensor self, Dimname dim, bool keepdim=False) -> (Tensor values, Tensor indices)");
|
||||
return table->getOp<std::tuple<Tensor,Tensor> (const Tensor &, Dimname, bool)>(at::detail::multi_dispatch_tensor_type_set(*this))(const_cast<Tensor&>(*this), dim, keepdim);
|
||||
#endif
|
||||
}
|
||||
#endif
|
||||
inline Tensor Tensor::mul(const Tensor & other) const {
|
||||
#ifdef USE_STATIC_DISPATCH
|
||||
switch(tensorTypeIdToBackend(impl::dispatchTypeId(type_set()))) {
|
||||
|
|
@ -2272,6 +2352,16 @@ inline Tensor Tensor::squeeze(int64_t dim) const {
|
|||
op, impl::dispatchTypeId(at::detail::multi_dispatch_tensor_type_set(*this)), const_cast<Tensor&>(*this), dim);
|
||||
#endif
|
||||
}
|
||||
#ifdef BUILD_NAMEDTENSOR
|
||||
inline Tensor Tensor::squeeze(Dimname dim) const {
|
||||
#ifdef USE_STATIC_DISPATCH
|
||||
return TypeDefault::squeeze(const_cast<Tensor&>(*this), dim);
|
||||
#else
|
||||
static auto table = globalATenDispatch().getOpTable("aten::squeeze.dimname(Tensor(a) self, Dimname dim) -> Tensor(a)");
|
||||
return table->getOp<Tensor (const Tensor &, Dimname)>(at::detail::multi_dispatch_tensor_type_set(*this))(const_cast<Tensor&>(*this), dim);
|
||||
#endif
|
||||
}
|
||||
#endif
|
||||
inline Tensor & Tensor::squeeze_() const {
|
||||
#ifdef USE_STATIC_DISPATCH
|
||||
return TypeDefault::squeeze_(const_cast<Tensor&>(*this));
|
||||
|
|
@ -2290,6 +2380,16 @@ inline Tensor & Tensor::squeeze_(int64_t dim) const {
|
|||
op, impl::dispatchTypeId(at::detail::multi_dispatch_tensor_type_set(*this)), const_cast<Tensor&>(*this), dim);
|
||||
#endif
|
||||
}
|
||||
#ifdef BUILD_NAMEDTENSOR
|
||||
inline Tensor & Tensor::squeeze_(Dimname dim) const {
|
||||
#ifdef USE_STATIC_DISPATCH
|
||||
return TypeDefault::squeeze_(const_cast<Tensor&>(*this), dim);
|
||||
#else
|
||||
static auto table = globalATenDispatch().getOpTable("aten::squeeze_.dimname(Tensor(a!) self, Dimname dim) -> Tensor(a!)");
|
||||
return table->getOp<Tensor & (Tensor &, Dimname)>(at::detail::multi_dispatch_tensor_type_set(*this))(const_cast<Tensor&>(*this), dim);
|
||||
#endif
|
||||
}
|
||||
#endif
|
||||
inline Tensor Tensor::sspaddmm(const Tensor & mat1, const Tensor & mat2, Scalar beta, Scalar alpha) const {
|
||||
#ifdef USE_STATIC_DISPATCH
|
||||
return TypeDefault::sspaddmm(const_cast<Tensor&>(*this), mat1, mat2, beta, alpha);
|
||||
|
|
@ -3574,6 +3674,16 @@ inline Tensor Tensor::index_add(int64_t dim, const Tensor & index, const Tensor
|
|||
op, impl::dispatchTypeId(at::detail::multi_dispatch_tensor_type_set(*this, index, source)), const_cast<Tensor&>(*this), dim, index, source);
|
||||
#endif
|
||||
}
|
||||
#ifdef BUILD_NAMEDTENSOR
|
||||
inline Tensor Tensor::index_add(Dimname dim, const Tensor & index, const Tensor & source) const {
|
||||
#ifdef USE_STATIC_DISPATCH
|
||||
return TypeDefault::index_add(const_cast<Tensor&>(*this), dim, index, source);
|
||||
#else
|
||||
static auto table = globalATenDispatch().getOpTable("aten::index_add.dimname(Tensor self, Dimname dim, Tensor index, Tensor source) -> Tensor");
|
||||
return table->getOp<Tensor (const Tensor &, Dimname, const Tensor &, const Tensor &)>(at::detail::multi_dispatch_tensor_type_set(*this, index, source))(const_cast<Tensor&>(*this), dim, index, source);
|
||||
#endif
|
||||
}
|
||||
#endif
|
||||
inline Tensor & Tensor::index_fill_(int64_t dim, const Tensor & index, Scalar value) const {
|
||||
#ifdef USE_STATIC_DISPATCH
|
||||
switch(tensorTypeIdToBackend(impl::dispatchTypeId(type_set()))) {
|
||||
|
|
@ -3622,6 +3732,26 @@ inline Tensor Tensor::index_fill(int64_t dim, const Tensor & index, const Tensor
|
|||
op, impl::dispatchTypeId(at::detail::multi_dispatch_tensor_type_set(*this, index, value)), const_cast<Tensor&>(*this), dim, index, value);
|
||||
#endif
|
||||
}
|
||||
#ifdef BUILD_NAMEDTENSOR
|
||||
inline Tensor Tensor::index_fill(Dimname dim, const Tensor & index, Scalar value) const {
|
||||
#ifdef USE_STATIC_DISPATCH
|
||||
return TypeDefault::index_fill(const_cast<Tensor&>(*this), dim, index, value);
|
||||
#else
|
||||
static auto table = globalATenDispatch().getOpTable("aten::index_fill.dimname_Scalar(Tensor self, Dimname dim, Tensor index, Scalar value) -> Tensor");
|
||||
return table->getOp<Tensor (const Tensor &, Dimname, const Tensor &, Scalar)>(at::detail::multi_dispatch_tensor_type_set(*this, index))(const_cast<Tensor&>(*this), dim, index, value);
|
||||
#endif
|
||||
}
|
||||
#endif
|
||||
#ifdef BUILD_NAMEDTENSOR
|
||||
inline Tensor Tensor::index_fill(Dimname dim, const Tensor & index, const Tensor & value) const {
|
||||
#ifdef USE_STATIC_DISPATCH
|
||||
return TypeDefault::index_fill(const_cast<Tensor&>(*this), dim, index, value);
|
||||
#else
|
||||
static auto table = globalATenDispatch().getOpTable("aten::index_fill.dimname_Tensor(Tensor self, Dimname dim, Tensor index, Tensor value) -> Tensor");
|
||||
return table->getOp<Tensor (const Tensor &, Dimname, const Tensor &, const Tensor &)>(at::detail::multi_dispatch_tensor_type_set(*this, index, value))(const_cast<Tensor&>(*this), dim, index, value);
|
||||
#endif
|
||||
}
|
||||
#endif
|
||||
inline Tensor & Tensor::scatter_(int64_t dim, const Tensor & index, const Tensor & src) const {
|
||||
#ifdef USE_STATIC_DISPATCH
|
||||
switch(tensorTypeIdToBackend(impl::dispatchTypeId(type_set()))) {
|
||||
|
|
@ -3670,6 +3800,26 @@ inline Tensor Tensor::scatter(int64_t dim, const Tensor & index, Scalar value) c
|
|||
op, impl::dispatchTypeId(at::detail::multi_dispatch_tensor_type_set(*this, index)), const_cast<Tensor&>(*this), dim, index, value);
|
||||
#endif
|
||||
}
|
||||
#ifdef BUILD_NAMEDTENSOR
|
||||
inline Tensor Tensor::scatter(Dimname dim, const Tensor & index, const Tensor & src) const {
|
||||
#ifdef USE_STATIC_DISPATCH
|
||||
return TypeDefault::scatter(const_cast<Tensor&>(*this), dim, index, src);
|
||||
#else
|
||||
static auto table = globalATenDispatch().getOpTable("aten::scatter.dimname_src(Tensor self, Dimname dim, Tensor index, Tensor src) -> Tensor");
|
||||
return table->getOp<Tensor (const Tensor &, Dimname, const Tensor &, const Tensor &)>(at::detail::multi_dispatch_tensor_type_set(*this, index, src))(const_cast<Tensor&>(*this), dim, index, src);
|
||||
#endif
|
||||
}
|
||||
#endif
|
||||
#ifdef BUILD_NAMEDTENSOR
|
||||
inline Tensor Tensor::scatter(Dimname dim, const Tensor & index, Scalar value) const {
|
||||
#ifdef USE_STATIC_DISPATCH
|
||||
return TypeDefault::scatter(const_cast<Tensor&>(*this), dim, index, value);
|
||||
#else
|
||||
static auto table = globalATenDispatch().getOpTable("aten::scatter.dimname_value(Tensor self, Dimname dim, Tensor index, Scalar value) -> Tensor");
|
||||
return table->getOp<Tensor (const Tensor &, Dimname, const Tensor &, Scalar)>(at::detail::multi_dispatch_tensor_type_set(*this, index))(const_cast<Tensor&>(*this), dim, index, value);
|
||||
#endif
|
||||
}
|
||||
#endif
|
||||
inline Tensor & Tensor::scatter_add_(int64_t dim, const Tensor & index, const Tensor & src) const {
|
||||
#ifdef USE_STATIC_DISPATCH
|
||||
switch(tensorTypeIdToBackend(impl::dispatchTypeId(type_set()))) {
|
||||
|
|
@ -3694,6 +3844,16 @@ inline Tensor Tensor::scatter_add(int64_t dim, const Tensor & index, const Tenso
|
|||
op, impl::dispatchTypeId(at::detail::multi_dispatch_tensor_type_set(*this, index, src)), const_cast<Tensor&>(*this), dim, index, src);
|
||||
#endif
|
||||
}
|
||||
#ifdef BUILD_NAMEDTENSOR
|
||||
inline Tensor Tensor::scatter_add(Dimname dim, const Tensor & index, const Tensor & src) const {
|
||||
#ifdef USE_STATIC_DISPATCH
|
||||
return TypeDefault::scatter_add(const_cast<Tensor&>(*this), dim, index, src);
|
||||
#else
|
||||
static auto table = globalATenDispatch().getOpTable("aten::scatter_add.dimname(Tensor self, Dimname dim, Tensor index, Tensor src) -> Tensor");
|
||||
return table->getOp<Tensor (const Tensor &, Dimname, const Tensor &, const Tensor &)>(at::detail::multi_dispatch_tensor_type_set(*this, index, src))(const_cast<Tensor&>(*this), dim, index, src);
|
||||
#endif
|
||||
}
|
||||
#endif
|
||||
inline Tensor & Tensor::lt_(Scalar other) const {
|
||||
#ifdef USE_STATIC_DISPATCH
|
||||
switch(tensorTypeIdToBackend(impl::dispatchTypeId(type_set()))) {
|
||||
|
|
@ -4852,6 +5012,16 @@ inline Tensor Tensor::index_select(int64_t dim, const Tensor & index) const {
|
|||
op, impl::dispatchTypeId(at::detail::multi_dispatch_tensor_type_set(*this, index)), const_cast<Tensor&>(*this), dim, index);
|
||||
#endif
|
||||
}
|
||||
#ifdef BUILD_NAMEDTENSOR
|
||||
inline Tensor Tensor::index_select(Dimname dim, const Tensor & index) const {
|
||||
#ifdef USE_STATIC_DISPATCH
|
||||
return TypeDefault::index_select(const_cast<Tensor&>(*this), dim, index);
|
||||
#else
|
||||
static auto table = globalATenDispatch().getOpTable("aten::index_select.dimname(Tensor self, Dimname dim, Tensor index) -> Tensor");
|
||||
return table->getOp<Tensor (const Tensor &, Dimname, const Tensor &)>(at::detail::multi_dispatch_tensor_type_set(*this, index))(const_cast<Tensor&>(*this), dim, index);
|
||||
#endif
|
||||
}
|
||||
#endif
|
||||
inline Tensor Tensor::masked_select(const Tensor & mask) const {
|
||||
#ifdef USE_STATIC_DISPATCH
|
||||
switch(tensorTypeIdToBackend(impl::dispatchTypeId(type_set()))) {
|
||||
|
|
@ -4906,6 +5076,16 @@ inline Tensor Tensor::gather(int64_t dim, const Tensor & index, bool sparse_grad
|
|||
op, impl::dispatchTypeId(at::detail::multi_dispatch_tensor_type_set(*this, index)), const_cast<Tensor&>(*this), dim, index, sparse_grad);
|
||||
#endif
|
||||
}
|
||||
#ifdef BUILD_NAMEDTENSOR
|
||||
inline Tensor Tensor::gather(Dimname dim, const Tensor & index, bool sparse_grad) const {
|
||||
#ifdef USE_STATIC_DISPATCH
|
||||
return TypeDefault::gather(const_cast<Tensor&>(*this), dim, index, sparse_grad);
|
||||
#else
|
||||
static auto table = globalATenDispatch().getOpTable("aten::gather.dimname(Tensor self, Dimname dim, Tensor index, *, bool sparse_grad=False) -> Tensor");
|
||||
return table->getOp<Tensor (const Tensor &, Dimname, const Tensor &, bool)>(at::detail::multi_dispatch_tensor_type_set(*this, index))(const_cast<Tensor&>(*this), dim, index, sparse_grad);
|
||||
#endif
|
||||
}
|
||||
#endif
|
||||
inline Tensor Tensor::addcmul(const Tensor & tensor1, const Tensor & tensor2, Scalar value) const {
|
||||
#ifdef USE_STATIC_DISPATCH
|
||||
return TypeDefault::addcmul(const_cast<Tensor&>(*this), tensor1, tensor2, value);
|
||||
|
|
@ -5418,6 +5598,16 @@ inline std::tuple<Tensor,Tensor> Tensor::sort(int64_t dim, bool descending) cons
|
|||
op, impl::dispatchTypeId(at::detail::multi_dispatch_tensor_type_set(*this)), const_cast<Tensor&>(*this), dim, descending);
|
||||
#endif
|
||||
}
|
||||
#ifdef BUILD_NAMEDTENSOR
|
||||
inline std::tuple<Tensor,Tensor> Tensor::sort(Dimname dim, bool descending) const {
|
||||
#ifdef USE_STATIC_DISPATCH
|
||||
return TypeDefault::sort(const_cast<Tensor&>(*this), dim, descending);
|
||||
#else
|
||||
static auto table = globalATenDispatch().getOpTable("aten::sort.dimname(Tensor self, Dimname dim, bool descending=False) -> (Tensor values, Tensor indices)");
|
||||
return table->getOp<std::tuple<Tensor,Tensor> (const Tensor &, Dimname, bool)>(at::detail::multi_dispatch_tensor_type_set(*this))(const_cast<Tensor&>(*this), dim, descending);
|
||||
#endif
|
||||
}
|
||||
#endif
|
||||
inline Tensor Tensor::argsort(int64_t dim, bool descending) const {
|
||||
#ifdef USE_STATIC_DISPATCH
|
||||
return TypeDefault::argsort(const_cast<Tensor&>(*this), dim, descending);
|
||||
|
|
@ -5427,6 +5617,16 @@ inline Tensor Tensor::argsort(int64_t dim, bool descending) const {
|
|||
op, impl::dispatchTypeId(at::detail::multi_dispatch_tensor_type_set(*this)), const_cast<Tensor&>(*this), dim, descending);
|
||||
#endif
|
||||
}
|
||||
#ifdef BUILD_NAMEDTENSOR
|
||||
inline Tensor Tensor::argsort(Dimname dim, bool descending) const {
|
||||
#ifdef USE_STATIC_DISPATCH
|
||||
return TypeDefault::argsort(const_cast<Tensor&>(*this), dim, descending);
|
||||
#else
|
||||
static auto table = globalATenDispatch().getOpTable("aten::argsort.dimname(Tensor self, Dimname dim, bool descending=False) -> Tensor");
|
||||
return table->getOp<Tensor (const Tensor &, Dimname, bool)>(at::detail::multi_dispatch_tensor_type_set(*this))(const_cast<Tensor&>(*this), dim, descending);
|
||||
#endif
|
||||
}
|
||||
#endif
|
||||
inline std::tuple<Tensor,Tensor> Tensor::topk(int64_t k, int64_t dim, bool largest, bool sorted) const {
|
||||
#ifdef USE_STATIC_DISPATCH
|
||||
switch(tensorTypeIdToBackend(impl::dispatchTypeId(type_set()))) {
|
||||
|
|
|
|||
|
|
@ -232,5 +232,100 @@ Tensor unflatten(const Tensor& self, Dimname dim, IntArrayRef sizes, DimnameList
|
|||
return native::unflatten(self, dimname_to_position(self, dim), sizes, names);
|
||||
}
|
||||
|
||||
#ifdef BUILD_NAMEDTENSOR
|
||||
// Misc. Dimname overloads that don't have homes. Maybe we should move
|
||||
// all of them here or autogenerate them because they look so similar.
|
||||
Tensor gather(const Tensor& self, Dimname dim, const Tensor& index, bool sparse_grad) {
|
||||
reportNYIDimnameOverload("gather");
|
||||
}
|
||||
Tensor& gather_out(Tensor& result, const Tensor& self, Dimname dim, const Tensor& index, bool sparse_grad) {
|
||||
reportNYIDimnameOverload("gather");
|
||||
}
|
||||
std::tuple<Tensor, Tensor> mode(const Tensor& self, Dimname dim, bool keepdim) {
|
||||
reportNYIDimnameOverload("mode");
|
||||
}
|
||||
std::tuple<Tensor &,Tensor &> mode_out(Tensor& values, Tensor& indices,
|
||||
const Tensor& self, Dimname dim, bool keepdim) {
|
||||
reportNYIDimnameOverload("mode");
|
||||
}
|
||||
std::tuple<Tensor&, Tensor&> kthvalue_out(
|
||||
Tensor& values,
|
||||
Tensor& indices,
|
||||
const Tensor& self,
|
||||
int64_t k,
|
||||
Dimname dim,
|
||||
bool keepdim) {
|
||||
reportNYIDimnameOverload("kthvalue");
|
||||
}
|
||||
std::tuple<Tensor, Tensor> kthvalue(
|
||||
const Tensor& self,
|
||||
int64_t k,
|
||||
Dimname dim,
|
||||
bool keepdim) {
|
||||
reportNYIDimnameOverload("kthvalue");
|
||||
}
|
||||
Tensor index_add(const Tensor& self, Dimname dim, const Tensor& index, const Tensor& source) {
|
||||
reportNYIDimnameOverload("index_add");
|
||||
}
|
||||
Tensor& index_add_(Tensor& self, Dimname dim, const Tensor& index, const Tensor& source) {
|
||||
reportNYIDimnameOverload("index_add");
|
||||
}
|
||||
Tensor index_fill(const Tensor& self, Dimname dim, const Tensor& index, Scalar source) {
|
||||
reportNYIDimnameOverload("index_fill");
|
||||
}
|
||||
Tensor& index_fill_(Tensor& self, Dimname dim, const Tensor& index, Scalar source) {
|
||||
reportNYIDimnameOverload("index_fill");
|
||||
}
|
||||
Tensor index_fill(const Tensor& self, Dimname dim, const Tensor& index, const Tensor& source) {
|
||||
reportNYIDimnameOverload("index_fill");
|
||||
}
|
||||
Tensor& index_fill_(Tensor& self, Dimname dim, const Tensor& index, const Tensor& source) {
|
||||
reportNYIDimnameOverload("index_fill");
|
||||
}
|
||||
Tensor index_copy(const Tensor& self, Dimname dim, const Tensor& index, const Tensor& source) {
|
||||
reportNYIDimnameOverload("index_copy");
|
||||
}
|
||||
Tensor& index_copy_(Tensor& self, Dimname dim, const Tensor& index, const Tensor& source) {
|
||||
reportNYIDimnameOverload("index_copy");
|
||||
}
|
||||
Tensor& index_select_out(Tensor& out, const Tensor& self, Dimname dim, const Tensor& index) {
|
||||
reportNYIDimnameOverload("index_select");
|
||||
}
|
||||
Tensor index_select(const Tensor& self, Dimname dim, const Tensor& index) {
|
||||
reportNYIDimnameOverload("index_select");
|
||||
}
|
||||
Tensor scatter(const Tensor& self, Dimname dim, const Tensor& index, const Tensor& source) {
|
||||
reportNYIDimnameOverload("scatter");
|
||||
}
|
||||
Tensor& scatter_(Tensor& self, Dimname dim, const Tensor& index, const Tensor& source) {
|
||||
reportNYIDimnameOverload("scatter");
|
||||
}
|
||||
Tensor scatter(const Tensor& self, Dimname dim, const Tensor& index, Scalar source) {
|
||||
reportNYIDimnameOverload("scatter");
|
||||
}
|
||||
Tensor& scatter_(Tensor& self, Dimname dim, const Tensor& index, Scalar source) {
|
||||
reportNYIDimnameOverload("scatter");
|
||||
}
|
||||
Tensor scatter_add(const Tensor& self, Dimname dim, const Tensor& index, const Tensor& source) {
|
||||
reportNYIDimnameOverload("scatter_add");
|
||||
}
|
||||
Tensor& scatter_add_(Tensor& self, Dimname dim, const Tensor& index, const Tensor& source) {
|
||||
reportNYIDimnameOverload("scatter_add");
|
||||
}
|
||||
std::tuple<Tensor&, Tensor&> sort_out(Tensor& values, Tensor& indices, const Tensor& self, Dimname dim, bool keepdim) {
|
||||
reportNYIDimnameOverload("sort");
|
||||
}
|
||||
std::tuple<Tensor, Tensor> sort(const Tensor& self, Dimname dim, bool keepdim) {
|
||||
reportNYIDimnameOverload("sort");
|
||||
}
|
||||
Tensor& squeeze_(Tensor& self, Dimname dim) {
|
||||
reportNYIDimnameOverload("squeeze");
|
||||
}
|
||||
Tensor squeeze(const Tensor& self, Dimname dim) {
|
||||
reportNYIDimnameOverload("squeeze");
|
||||
}
|
||||
|
||||
#endif
|
||||
|
||||
}} // namespace at::native
|
||||
#endif
|
||||
|
|
|
|||
|
|
@ -716,6 +716,32 @@ Tensor norm(const Tensor& self, optional<Scalar> p, DimnameList dim, bool keepdi
|
|||
Tensor norm(const Tensor& self, optional<Scalar> p, DimnameList dim, bool keepdim) {
|
||||
return at::norm(self, p, dimnames_to_positions(self, dim), keepdim);
|
||||
}
|
||||
|
||||
Tensor any(const Tensor& self, Dimname dim, bool keepdim) {
|
||||
reportNYIDimnameOverload("any");
|
||||
}
|
||||
Tensor& any_out(Tensor& result, const Tensor &self, Dimname dim, bool keepdim) {
|
||||
reportNYIDimnameOverload("any");
|
||||
}
|
||||
Tensor all(const Tensor& self, Dimname dim, bool keepdim) {
|
||||
reportNYIDimnameOverload("all");
|
||||
}
|
||||
Tensor& all_out(Tensor& result, const Tensor &self, Dimname dim, bool keepdim) {
|
||||
reportNYIDimnameOverload("all");
|
||||
}
|
||||
Tensor cumsum(const Tensor& self, Dimname dim, c10::optional<ScalarType> dtype) {
|
||||
reportNYIDimnameOverload("cumsum");
|
||||
}
|
||||
Tensor& cumsum_out(Tensor& result, const Tensor& self, Dimname dim, c10::optional<ScalarType> dtype) {
|
||||
reportNYIDimnameOverload("cumsum");
|
||||
}
|
||||
Tensor cumprod(const Tensor& self, Dimname dim, c10::optional<ScalarType> dtype) {
|
||||
reportNYIDimnameOverload("cumprod");
|
||||
}
|
||||
Tensor& cumprod_out(Tensor& result, const Tensor& self, Dimname dim, c10::optional<ScalarType> dtype) {
|
||||
reportNYIDimnameOverload("cumprod");
|
||||
}
|
||||
|
||||
#endif
|
||||
|
||||
}} // namespace at::native
|
||||
|
|
|
|||
|
|
@ -275,6 +275,15 @@ std::tuple<Tensor &,Tensor &> max_out(Tensor& max, Tensor& max_indices,
|
|||
TORCH_CHECK(false, "NYI: max with names");
|
||||
return at::max_out(max, max_indices, self, dimname_to_position(self, dim), keepdim);
|
||||
}
|
||||
Tensor argmax(const Tensor& self, Dimname dim, bool keepdim) {
|
||||
reportNYIDimnameOverload("argmax");
|
||||
}
|
||||
Tensor argmin(const Tensor& self, Dimname dim, bool keepdim) {
|
||||
reportNYIDimnameOverload("argmin");
|
||||
}
|
||||
Tensor argsort(const Tensor& self, Dimname dim, bool keepdim) {
|
||||
reportNYIDimnameOverload("argsort");
|
||||
}
|
||||
#endif
|
||||
|
||||
}} // namespace at::native
|
||||
|
|
|
|||
|
|
@ -311,6 +311,11 @@
|
|||
|
||||
- func: all.out(Tensor self, int dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!)
|
||||
|
||||
- func: all.dimname(Tensor self, Dimname dim, bool keepdim=False) -> Tensor
|
||||
variants: function, method
|
||||
|
||||
- func: all.dimname_out(Tensor self, Dimname dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!)
|
||||
|
||||
- func: allclose(Tensor self, Tensor other, float rtol=1e-05, float atol=1e-08, bool equal_nan=False) -> bool
|
||||
use_c10_dispatcher: full
|
||||
variants: function, method
|
||||
|
|
@ -321,6 +326,11 @@
|
|||
|
||||
- func: any.out(Tensor self, int dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!)
|
||||
|
||||
- func: any.dimname(Tensor self, Dimname dim, bool keepdim=False) -> Tensor
|
||||
variants: function, method
|
||||
|
||||
- func: any.dimname_out(Tensor self, Dimname dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!)
|
||||
|
||||
- func: arange(Scalar end, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
|
||||
|
||||
- func: arange.start(Scalar start, Scalar end, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
|
||||
|
|
@ -821,11 +831,22 @@
|
|||
|
||||
- func: cumsum.out(Tensor self, int dim, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!)
|
||||
|
||||
- func: cumsum.dimname(Tensor self, Dimname dim, *, ScalarType? dtype=None) -> Tensor
|
||||
variants: function, method
|
||||
|
||||
- func: cumsum.dimname_out(Tensor self, Dimname dim, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!)
|
||||
|
||||
- func: cumprod(Tensor self, int dim, *, ScalarType? dtype=None) -> Tensor
|
||||
variants: function, method
|
||||
|
||||
- func: cumprod.out(Tensor self, int dim, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!)
|
||||
|
||||
- func: cumprod.dimname(Tensor self, Dimname dim, *, ScalarType? dtype=None) -> Tensor
|
||||
variants: function, method
|
||||
|
||||
- func: cumprod.dimname_out(Tensor self, Dimname dim, *, ScalarType? dtype=None, Tensor(a!) out) -> Tensor(a!)
|
||||
|
||||
|
||||
- func: ctc_loss.IntList(Tensor log_probs, Tensor targets, int[] input_lengths, int[] target_lengths, int blank=0, int reduction=Mean, bool zero_infinity=False) -> Tensor
|
||||
use_c10_dispatcher: unboxed_only
|
||||
|
||||
|
|
@ -1321,6 +1342,12 @@
|
|||
use_c10_dispatcher: full
|
||||
variants: function, method
|
||||
|
||||
- func: index_copy_.dimname(Tensor(a!) self, Dimname dim, Tensor index, Tensor source) -> Tensor(a!)
|
||||
variants: method
|
||||
|
||||
- func: index_copy.dimname(Tensor self, Dimname dim, Tensor index, Tensor source) -> Tensor
|
||||
variants: function, method
|
||||
|
||||
- func: index_put_(Tensor(a!) self, Tensor?[] indices, Tensor values, bool accumulate=False) -> Tensor(a!)
|
||||
variants: function, method
|
||||
|
||||
|
|
@ -1408,6 +1435,11 @@
|
|||
CPU: kthvalue_out_cpu
|
||||
CUDA: kthvalue_out_cuda
|
||||
|
||||
- func: kthvalue.dimname(Tensor self, int k, Dimname dim, bool keepdim=False) -> (Tensor values, Tensor indices)
|
||||
variants: function, method
|
||||
|
||||
- func: kthvalue.dimname_out(Tensor self, int k, Dimname dim, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices)
|
||||
|
||||
- func: layer_norm(Tensor input, int[] normalized_shape, Tensor? weight=None, Tensor? bias=None, float eps=1e-05, bool cudnn_enable=True) -> Tensor
|
||||
|
||||
- func: native_layer_norm(Tensor input, Tensor? weight, Tensor? bias, int M, int N, float eps) -> (Tensor, Tensor, Tensor)
|
||||
|
|
@ -1837,6 +1869,11 @@
|
|||
|
||||
- func: mode.values(Tensor self, int dim=-1, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices)
|
||||
|
||||
- func: mode.dimname(Tensor self, Dimname dim, bool keepdim=False) -> (Tensor values, Tensor indices)
|
||||
variants: function, method
|
||||
|
||||
- func: mode.dimname_out(Tensor self, Dimname dim, bool keepdim=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices)
|
||||
|
||||
- func: mul.Tensor(Tensor self, Tensor other) -> Tensor
|
||||
use_c10_dispatcher: full
|
||||
variants: function, method
|
||||
|
|
@ -2463,6 +2500,10 @@
|
|||
variants: function, method
|
||||
device_guard: False
|
||||
|
||||
- func: squeeze.dimname(Tensor(a) self, Dimname dim) -> Tensor(a)
|
||||
variants: function, method
|
||||
device_guard: False
|
||||
|
||||
- func: squeeze_(Tensor(a!) self) -> Tensor(a!)
|
||||
use_c10_dispatcher: unboxed_only
|
||||
variants: method
|
||||
|
|
@ -2473,6 +2514,10 @@
|
|||
variants: method
|
||||
device_guard: False
|
||||
|
||||
- func: squeeze_.dimname(Tensor(a!) self, Dimname dim) -> Tensor(a!)
|
||||
variants: method
|
||||
device_guard: False
|
||||
|
||||
- func: sspaddmm(Tensor self, Tensor mat1, Tensor mat2, *, Scalar beta=1, Scalar alpha=1) -> Tensor
|
||||
use_c10_dispatcher: full
|
||||
variants: function, method
|
||||
|
|
@ -2995,7 +3040,6 @@
|
|||
|
||||
- func: norm.names_out(Tensor self, Scalar? p, Dimname[1] dim, bool keepdim=False, *, Tensor(a!) out) -> Tensor(a!)
|
||||
|
||||
|
||||
- func: frobenius_norm(Tensor self) -> Tensor
|
||||
use_c10_dispatcher: full
|
||||
variants: function
|
||||
|
|
@ -3843,6 +3887,9 @@
|
|||
use_c10_dispatcher: full
|
||||
variants: function, method
|
||||
|
||||
- func: index_add.dimname(Tensor self, Dimname dim, Tensor index, Tensor source) -> Tensor
|
||||
variants: function, method
|
||||
|
||||
- func: index_fill_.Scalar(Tensor(a!) self, int dim, Tensor index, Scalar value) -> Tensor(a!)
|
||||
use_c10_dispatcher: unboxed_only
|
||||
variants: method
|
||||
|
|
@ -3865,6 +3912,12 @@
|
|||
use_c10_dispatcher: full
|
||||
variants: function, method
|
||||
|
||||
- func: index_fill.dimname_Scalar(Tensor self, Dimname dim, Tensor index, Scalar value) -> Tensor
|
||||
variants: function, method
|
||||
|
||||
- func: index_fill.dimname_Tensor(Tensor self, Dimname dim, Tensor index, Tensor value) -> Tensor
|
||||
variants: function, method
|
||||
|
||||
- func: scatter_.src(Tensor(a!) self, int dim, Tensor index, Tensor src) -> Tensor(a!)
|
||||
use_c10_dispatcher: unboxed_only
|
||||
variants: method
|
||||
|
|
@ -3887,6 +3940,12 @@
|
|||
use_c10_dispatcher: full
|
||||
variants: function, method
|
||||
|
||||
- func: scatter.dimname_src(Tensor self, Dimname dim, Tensor index, Tensor src) -> Tensor
|
||||
variants: function, method
|
||||
|
||||
- func: scatter.dimname_value(Tensor self, Dimname dim, Tensor index, Scalar value) -> Tensor
|
||||
variants: function, method
|
||||
|
||||
- func: scatter_add_(Tensor(a!) self, int dim, Tensor index, Tensor src) -> Tensor(a!)
|
||||
use_c10_dispatcher: unboxed_only
|
||||
variants: method
|
||||
|
|
@ -3898,6 +3957,9 @@
|
|||
use_c10_dispatcher: full
|
||||
variants: function, method
|
||||
|
||||
- func: scatter_add.dimname(Tensor self, Dimname dim, Tensor index, Tensor src) -> Tensor
|
||||
variants: function, method
|
||||
|
||||
- func: lt_.Scalar(Tensor(a!) self, Scalar other) -> Tensor(a!)
|
||||
use_c10_dispatcher: unboxed_only
|
||||
variants: method
|
||||
|
|
@ -4558,6 +4620,11 @@
|
|||
SparseCPU: index_select_sparse
|
||||
SparseCUDA: index_select_sparse
|
||||
|
||||
- func: index_select.dimname_out(Tensor self, Dimname dim, Tensor index, *, Tensor(a!) out) -> Tensor(a!)
|
||||
|
||||
- func: index_select.dimname(Tensor self, Dimname dim, Tensor index) -> Tensor
|
||||
variants: method, function
|
||||
|
||||
- func: masked_select.out(Tensor self, Tensor mask, *, Tensor(a!) out) -> Tensor(a!)
|
||||
dispatch:
|
||||
CPU: masked_select_out_cpu
|
||||
|
|
@ -4600,6 +4667,11 @@
|
|||
CPU: gather_cpu
|
||||
CUDA: gather_cuda
|
||||
|
||||
- func: gather.dimname_out(Tensor self, Dimname dim, Tensor index, *, bool sparse_grad=False, Tensor(a!) out) -> Tensor(a!)
|
||||
|
||||
- func: gather.dimname(Tensor self, Dimname dim, Tensor index, *, bool sparse_grad=False) -> Tensor
|
||||
variants: method, function
|
||||
|
||||
- func: _gather_sparse_backward(Tensor self, int dim, Tensor index, Tensor grad) -> Tensor
|
||||
use_c10_dispatcher: full
|
||||
|
||||
|
|
@ -5048,10 +5120,18 @@
|
|||
CUDA: legacy::cuda::_th_sort
|
||||
QuantizedCPU: sort_quant
|
||||
|
||||
- func: sort.dimname_values(Tensor self, Dimname dim, bool descending=False, *, Tensor(a!) values, Tensor(b!) indices) -> (Tensor(a!) values, Tensor(b!) indices)
|
||||
|
||||
- func: sort.dimname(Tensor self, Dimname dim, bool descending=False) -> (Tensor values, Tensor indices)
|
||||
variants: method, function
|
||||
|
||||
- func: argsort(Tensor self, int dim=-1, bool descending=False) -> Tensor
|
||||
use_c10_dispatcher: full
|
||||
variants: method, function
|
||||
|
||||
- func: argsort.dimname(Tensor self, Dimname dim, bool descending=False) -> Tensor
|
||||
variants: method, function
|
||||
|
||||
- func: topk.values(Tensor self, int k, int dim=-1, bool largest=True, bool sorted=True, *, Tensor(a!) values, Tensor(b!) indices) ->(Tensor(a!) values, Tensor(b!) indices)
|
||||
dispatch:
|
||||
CPU: topk_out_cpu
|
||||
|
|
|
|||
|
|
@ -1682,6 +1682,11 @@ class TestNamedTensor(TestCase):
|
|||
self.assertTrue(
|
||||
str(warns[0].message).startswith('Autograd was passed a named grad tensor'))
|
||||
|
||||
def test_nyi_dimname_overload_msg(self):
|
||||
x = torch.randn(3, 3)
|
||||
with self.assertRaisesRegex(RuntimeError, "squeeze: You passed a dimname"):
|
||||
x.squeeze("N")
|
||||
|
||||
def test_dot(self):
|
||||
for device in torch.testing.get_all_device_types():
|
||||
# torch.dot ignores the names of both tensors
|
||||
|
|
|
|||
Loading…
Reference in New Issue
Block a user