Resend diff D23858329 (#45315)

Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/45315

Pull Request resolved: https://github.com/pytorch/pytorch/pull/45314

in D23858329 (721cfbf842), we put PriorCorrectionCalibrationPrediction unit test in OSS file which causes test failure issue in public trunk.

this diff moves it to FB only test file.

Test Plan:
```
 buck test //caffe2/caffe2/python/operator_test:torch_integration_test -- test_gather_ranges_to_dense_op

buck test //caffe2/caffe2/fb/python/operator_test:torch_integration_test -- test_prior_correct_calibration_prediction_op
```
all pass.

Reviewed By: houseroad

Differential Revision: D23899012

fbshipit-source-id: 1ed97d8702e2765991e6caf5695d4c49353dae82

caffe2/operators/gather_ranges_to_dense_op.cc

@@ -104,3 +104,11 @@ NO_GRADIENT(GatherRangesToDense);
 
 } // namespace
 } // namespace caffe2
+
+using GatherRangesToDenseCPUOp =
+    caffe2::GatherRangesToDenseOp<caffe2::CPUContext>;
+
+C10_EXPORT_CAFFE2_OP_TO_C10_CPU(
+    GatherRangesToDense,
+    "_caffe2::GatherRangesToDense(Tensor data, Tensor ranges, Tensor? key, int[] lengths, int min_observation, float max_mismatched_ratio, float max_empty_ratio) -> Tensor[] outputs",
+    GatherRangesToDenseCPUOp);

caffe2/operators/gather_ranges_to_dense_op.h

@@ -5,6 +5,7 @@
 
 #include "caffe2/core/common_omp.h"
 #include "caffe2/core/context.h"
+#include "caffe2/core/export_caffe2_op_to_c10.h"
 #include "caffe2/core/logging.h"
 #include "caffe2/core/operator.h"
 #include "caffe2/core/types.h"
@@ -15,6 +16,8 @@
 #include <map>
 #include <utility>
 
+C10_DECLARE_EXPORT_CAFFE2_OP_TO_C10(GatherRangesToDense);
+
 namespace caffe2 {
 template <class Context>
 class GatherRangesToDenseOp final : public Operator<Context> {

caffe2/python/operator_test/torch_integration_test.py

@@ -875,6 +875,47 @@ class TorchIntegration(hu.HypothesisTestCase):
         )
         torch.testing.assert_allclose(expected_output, actual_output.cpu())
 
+    def test_gather_ranges_to_dense_op(self):
+        data = np.array([1, 2, 3, 4, 5, 6, 7, 8])
+        ranges = np.array([[[2, 4]], [[0, 0]]])
+        key = np.array([0, 1, 3, 2, 1, 0, 1, 0])
+        lengths = np.array([4])
+        min_observation = 2
+        max_mismatched_ratio = 0.5
+        max_empty_ratio = 1.0
+
+        outputs_name = ["X_{}".format(i) for i in range(len(lengths))]
+        ref_op = core.CreateOperator(
+            "GatherRangesToDense",
+            ["data", "ranges", "key"],
+            outputs_name,
+            lengths=lengths,
+            min_observation=min_observation,
+            max_mismatched_ratio=max_mismatched_ratio,
+            max_empty_ratio=max_empty_ratio,
+        )
+        workspace.FeedBlob("data", data)
+        workspace.FeedBlob("ranges", ranges)
+        workspace.FeedBlob("key", key)
+        workspace.RunOperatorOnce(ref_op)
+        ref_outputs = []
+        for output_name in outputs_name:
+            ref_outputs.append(workspace.FetchBlob(output_name))
+
+        outputs = torch.ops._caffe2.GatherRangesToDense(
+            torch.from_numpy(data),
+            torch.from_numpy(ranges),
+            torch.from_numpy(key),
+            lengths=lengths,
+            min_observation=min_observation,
+            max_mismatched_ratio=max_mismatched_ratio,
+            max_empty_ratio=max_empty_ratio,
+        )
+
+        self.assertEqual(len(ref_outputs), len(outputs))
+        for i in range(0, len(ref_outputs)):
+            np.testing.assert_array_almost_equal(ref_outputs[i], outputs[i].numpy())
+
     @given(lengths_0=st.integers(1, 10), lengths_1=st.integers(1, 10))
     @settings(deadline=1000)
     def test_merge_id_lists(self, lengths_0, lengths_1):