dock DepthwiseConv2dBackprop DepthwiseConv2dBackpropFilter DepthwiseConv2dBackpropInput

mindspore/ccsrc/kernel/tbe/tbe_adapter.cc

@@ -39,6 +39,9 @@ static std::map<string, string> tbe_func_adapter_map = {
   {"reduce_min", "reduce_min_d"},
   {"conv2d_backprop_filter", "conv2d_backprop_filter_d"},
   {"conv2d_backprop_input", "conv2d_backprop_input_d"},
+  {"depthwise_conv2d_native", "depthwise_conv2d"},
+  {"depthwise_conv2d_native_backprop_filter", "depthwise_conv2d_backprop_filter_d"},
+  {"depthwise_conv2d_native_backprop_input", "depthwise_conv2d_backprop_input_d"},
   {"top_kv2", "top_k"},
   {"scatter_nd", "scatter_nd_d"},
   {"tile", "tile_d"},

mindspore/ccsrc/pre_activate/pass/const_input_to_attr_registry.cc

@@ -27,6 +27,8 @@ ConstInputToAttrInfoRegistry::ConstInputToAttrInfoRegistry() {
   Register(prim::kPrimCast->name(), {1});
   Register(prim::kPrimConv2DBackpropInput->name(), {2});
   Register(prim::kPrimConv2DBackpropFilter->name(), {2});
+  Register(prim::kPrimDepthwiseConv2dNativeBackpropFilter->name(), {1});
+  Register(prim::kPrimDepthwiseConv2dNativeBackpropInput->name(), {0});
   Register(prim::kPrimReshape->name(), {1});
   Register(prim::kPrimReduceMax->name(), {1});
   Register(prim::kPrimReduceMin->name(), {1});

mindspore/ops/_op_impl/tbe/__init__.py

@@ -133,3 +133,6 @@ from .arg_min_with_value import _arg_min_with_value_tbe
 from .fused_mul_add import _fused_mul_add_tbe
 from .fused_mul_add_n import _fused_mul_add_n_tbe
 from .fused_mul_apply_momentum import _fused_mul_apply_momentum_tbe
+from .depthwise_conv2d import _depthwise_conv2d_tbe
+from .depthwise_conv2d_backprop_filter import _depthwise_conv2d_backprop_filter_tbe
+from .depthwise_conv2d_backprop_input import _depthwise_conv2d_backprop_input_tbe

mindspore/ops/_op_impl/tbe/depthwise_conv2d.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.
+# ============================================================================
+
+"""DepthwiseConv2D op"""
+from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
+
+depthwise_conv2d_op_info = TBERegOp("DepthwiseConv2dNative") \
+    .fusion_type("CONVLUTION") \
+    .async_flag(False) \
+    .binfile_name("depthwise_conv2d.so") \
+    .compute_cost(10) \
+    .kernel_name("depthwise_conv2d") \
+    .partial_flag(True) \
+    .attr("stride", "required", "listInt", "all") \
+    .attr("dilation", "required", "listInt", "all") \
+    .attr("pads", "required", "listInt", "all") \
+    .attr("data_format", "required", "str", "all") \
+    .attr("offset_a", "optional", "int", "all") \
+    .input(0, "x", False, "required", "all") \
+    .input(1, "filter", False, "required", "all") \
+    .input(2, "bias", False, "optional", "all") \
+    .input(3, "offset_w", False, "optional", "all") \
+    .output(0, "y", True, "required", "all") \
+    .dtype_format(DataType.F16_5HD, DataType.F16_C1HWNCoC0, DataType.F16_Default, DataType.F16_Default,
+                  DataType.F16_5HD) \
+    .get_op_info()
+
+
+@op_info_register(depthwise_conv2d_op_info)
+def _depthwise_conv2d_tbe():
+    """DepthwiseConv2D TBE register"""
+    return

mindspore/ops/_op_impl/tbe/depthwise_conv2d_backprop_filter.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.
+# ============================================================================
+
+"""DepthwiseConv2DBackpropFilter op"""
+from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
+
+depthwise_conv2d_backprop_filter_op_info = TBERegOp("DepthwiseConv2dNativeBackpropFilter") \
+    .fusion_type("CONVLUTION") \
+    .async_flag(False) \
+    .binfile_name("depthwise_conv2d_backprop_filter_d.so") \
+    .compute_cost(10) \
+    .kernel_name("depthwise_conv2d_backprop_filter_d") \
+    .partial_flag(True) \
+    .attr("filter_size", "required", "listInt", "all") \
+    .attr("stride", "required", "listInt", "all") \
+    .attr("dilation", "required", "listInt", "all") \
+    .attr("pads", "required", "str", "all") \
+    .attr("data_format", "required", "str", "all") \
+    .input(0, "input", False, "required", "all") \
+    .input(1, "out_backprop", False, "required", "all") \
+    .output(0, "filter_grad", False, "required", "all") \
+    .dtype_format(DataType.F16_5HD, DataType.F16_5HD, DataType.F32_C1HWNCoC0) \
+    .get_op_info()
+
+
+@op_info_register(depthwise_conv2d_backprop_filter_op_info)
+def _depthwise_conv2d_backprop_filter_tbe():
+    """DepthwiseConv2DBackpropFilter TBE register"""
+    return

mindspore/ops/_op_impl/tbe/depthwise_conv2d_backprop_input.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.
+# ============================================================================
+
+"""DepthwiseConv2DBackpropInput op"""
+from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
+
+depthwise_conv2d_backprop_input_op_info = TBERegOp("DepthwiseConv2dNativeBackpropInput") \
+    .fusion_type("CONVLUTION") \
+    .async_flag(False) \
+    .binfile_name("depthwise_conv2d_backprop_input_d.so") \
+    .compute_cost(10) \
+    .kernel_name("depthwise_conv2d_backprop_input_d") \
+    .partial_flag(True) \
+    .attr("input_size", "required", "listInt", "all") \
+    .attr("stride", "required", "listInt", "all") \
+    .attr("dilation", "required", "listInt", "all") \
+    .attr("pads", "required", "str", "all") \
+    .attr("data_format", "required", "str", "all") \
+    .input(0, "filter", False, "required", "all") \
+    .input(1, "out_backprop", False, "required", "all") \
+    .output(0, "input_grad", False, "required", "all") \
+    .dtype_format(DataType.F16_C1HWNCoC0, DataType.F16_5HD, DataType.F16_5HD) \
+    .get_op_info()
+
+
+@op_info_register(depthwise_conv2d_backprop_input_op_info)
+def _depthwise_conv2d_backprop_input_tbe():
+    """DepthwiseConv2DBackpropInput TBE register"""
+    return

mindspore/ops/operations/nn_ops.py

@@ -696,6 +696,7 @@ class DepthwiseConv2dNative(PrimitiveWithInfer):
                  dilation=1,
                  group=1):
         """init DepthwiseConv2dNative"""
+        self.init_prim_io_names(inputs=['x', 'w'], outputs=['output'])
         validator.check_pad_value_by_mode(self.__class__.__name__, pad_mode, pad)
         self.kernel_size = validator.check_type('kernel_size', kernel_size, (int, tuple))
         if isinstance(kernel_size, int):