!1302 Complete vm ops for BinaryCrossEntropy and BinaryCrossEntropyGrad

Merge pull request !1302 from lihongkang/master

mindspore/ops/_op_impl/tbe/__init__.py

@@ -189,3 +189,5 @@ from .pack import _pack_tbe
 from .unpack import _unpack_tbe
 from .prelu import _prelu_tbe
 from .prelu_grad import _prelu_grad_tbe
+from .binary_cross_entropy import _binary_cross_entropy_tbe
+from .binary_cross_entropy_grad import _binary_cross_entropy_grad_tbe

mindspore/ops/_op_impl/tbe/binary_cross_entropy.py

@@ -0,0 +1,41 @@
+# Copyright 2020 Huawei Technologies Co., Ltd
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ============================================================================
+
+"""BinaryCrossEntropy op"""
+from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
+
+binary_cross_entropy_op_info = TBERegOp("BinaryCrossEntropy") \
+    .fusion_type("OPAQUE") \
+    .async_flag(False) \
+    .binfile_name("binary_cross_entropy.so") \
+    .compute_cost(10) \
+    .kernel_name("binary_cross_entropy") \
+    .partial_flag(True) \
+    .attr("reduction", "optional", "str", "all") \
+    .input(0, "x", False, "required", "all") \
+    .input(1, "y", False, "required", "all") \
+    .input(2, "weight", False, "optional", "all") \
+    .output(0, "output", False, "required", "all") \
+    .dtype_format(DataType.F16_Default, DataType.F16_Default, DataType.F16_Default, DataType.F16_Default) \
+    .dtype_format(DataType.F16_5HD, DataType.F16_5HD, DataType.F16_5HD, DataType.F16_5HD) \
+    .dtype_format(DataType.F32_Default, DataType.F32_Default, DataType.F32_Default, DataType.F32_Default) \
+    .dtype_format(DataType.F32_5HD, DataType.F32_5HD, DataType.F32_5HD, DataType.F32_5HD) \
+    .get_op_info()
+
+
+@op_info_register(binary_cross_entropy_op_info)
+def _binary_cross_entropy_tbe():
+    """BinaryCrossEntropy TBE register"""
+    return

mindspore/ops/_op_impl/tbe/binary_cross_entropy_grad.py

@@ -0,0 +1,44 @@
+# Copyright 2020 Huawei Technologies Co., Ltd
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ============================================================================
+
+"""BinaryCrossEntropyGrad op"""
+from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
+
+binary_cross_entropy_grad_op_info = TBERegOp("BinaryCrossEntropyGrad") \
+    .fusion_type("OPAQUE") \
+    .async_flag(False) \
+    .binfile_name("binary_cross_entropy_grad.so") \
+    .compute_cost(10) \
+    .kernel_name("binary_cross_entropy_grad") \
+    .partial_flag(True) \
+    .attr("reduction", "optional", "str", "all") \
+    .input(0, "x", False, "required", "all") \
+    .input(1, "y", False, "required", "all") \
+    .input(2, "grad_output", False, "required", "all") \
+    .input(3, "weight", False, "optional", "all") \
+    .output(0, "output", False, "required", "all") \
+    .dtype_format(DataType.F16_Default, DataType.F16_Default, DataType.F16_Default, DataType.F16_Default,
+                  DataType.F16_Default) \
+    .dtype_format(DataType.F16_5HD, DataType.F16_5HD, DataType.F16_5HD, DataType.F16_5HD, DataType.F16_5HD) \
+    .dtype_format(DataType.F32_Default, DataType.F32_Default, DataType.F32_Default, DataType.F32_Default,
+                  DataType.F32_Default) \
+    .dtype_format(DataType.F32_5HD, DataType.F32_5HD, DataType.F32_5HD, DataType.F32_5HD, DataType.F32_5HD) \
+    .get_op_info()
+
+
+@op_info_register(binary_cross_entropy_grad_op_info)
+def _binary_cross_entropy_grad_tbe():
+    """BinaryCrossEntropyGrad TBE register"""
+    return

tests/ut/python/ops/test_ops.py

@@ -972,6 +972,19 @@ test_case_nn_ops = [
         'desc_inputs': [[3, 3], [3, 3], Tensor(0.001, mstype.float32), [3, 3], Tensor(0.1, mstype.float32), [3, 3]],
         'desc_bprop': [3, 3],
         'skip': ['backward']}),
+    ('BinaryCrossEntropy', {
+        'block': P.BinaryCrossEntropy(),
+        'desc_inputs': [Tensor([[0.3, 0.8], [0.4, 0.3]], mstype.float16),
+                        Tensor([[0.4, 1.2], [-0.4, -0.9]], mstype.float16),
+                        Tensor([[-1.4, -0.7], [0.9, 0.7]], mstype.float16)],
+        'desc_bprop': []}),
+    ('BinaryCrossEntropyGrad', {
+        'block': G.BinaryCrossEntropyGrad(),
+        'desc_inputs': [Tensor([[0.3, 0.8], [0.4, 0.3]], mstype.float16),
+                        Tensor([[0.4, 1.2], [-0.4, -0.9]], mstype.float16), Tensor(0.85, mstype.float16),
+                        Tensor([[-1.4, -0.7], [0.9, 0.7]], mstype.float16)],
+        'desc_bprop': [],
+        'skip': ['backward']}),
 ]
 
 test_case_array_ops = [