!224 Dock relu6 and relu6grad for open source process

Merge pull request !224 from zhangbuxue/dock_relu6_for_open_source_processes

mindspore/ccsrc/kernel/tbe/tbe_adapter.cc

@@ -30,6 +30,8 @@ namespace mindspore {
 namespace kernel {
 namespace tbe {
 static std::map<string, string> tbe_func_adapter_map = {
+  {"re_lu6", "relu6"},
+  {"re_lu6_grad", "relu6_grad"},
   {"re_lu", "relu"},
   {"tensor_add", "add"},
   {"reduce_mean", "reduce_mean_d"},

mindspore/ops/_grad/grad_math_ops.py

@@ -340,9 +340,9 @@ def get_bprop_pow(self):
     ln = P.Log()
 
     def bprop(x, power, out, dout):
-        dx = power * pow_op(x, power - 1.0) * dout
-        dpower = pow_op(x, power) * ln(x) * dout
-        return dx, dpower
+        bc_dx = power * pow_op(x, power - 1.0) * dout
+        bc_dpower = out * ln(x) * dout
+        return binop_grad_common(x, power, bc_dx, bc_dpower)
     return bprop
 
 

mindspore/ops/_op_impl/tbe/__init__.py

@@ -42,6 +42,8 @@ from .mul import _mul_tbe
 from .real_div import _real_div_tbe
 from .relu import _relu_tbe
 from .relu_grad import _relu_grad_tbe
+from .relu6 import _relu6_tbe
+from .relu6_grad import _relu6_grad_tbe
 from .softmax_cross_entropy_with_logits import _softmax_cross_entropy_with_logits_tbe
 from .sigmoid_cross_entropy_with_logits import _sigmoid_cross_entropy_with_logits_tbe
 from .sigmoid_cross_entropy_with_logits_grad import _sigmoid_cross_entropy_with_logits_grad_tbe

mindspore/ops/_op_impl/tbe/relu6.py

@@ -0,0 +1,40 @@
+# 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.
+# ============================================================================
+
+"""ReLU6 op"""
+from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
+
+relu6_op_info = TBERegOp("ReLU6") \
+    .fusion_type("ELEMWISE") \
+    .async_flag(False) \
+    .binfile_name("relu6.so") \
+    .compute_cost(10) \
+    .kernel_name("relu6") \
+    .partial_flag(True) \
+    .input(0, "features", False, "required", "all") \
+    .output(0, "activations", False, "required", "all") \
+    .dtype_format(DataType.F16_Default, DataType.F16_Default) \
+    .dtype_format(DataType.F16_5HD, DataType.F16_5HD) \
+    .dtype_format(DataType.F32_Default, DataType.F32_Default) \
+    .dtype_format(DataType.F32_5HD, DataType.F32_5HD) \
+    .dtype_format(DataType.I32_Default, DataType.I32_Default) \
+    .dtype_format(DataType.I32_5HD, DataType.I32_5HD) \
+    .get_op_info()
+
+
+@op_info_register(relu6_op_info)
+def _relu6_tbe():
+    """Relu6 TBE register"""
+    return

mindspore/ops/_op_impl/tbe/relu6_grad.py

@@ -0,0 +1,43 @@
+# 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.
+# ============================================================================
+
+"""ReLU6Grad op"""
+from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
+
+relu6_grad_op_info = TBERegOp("ReLU6Grad") \
+    .fusion_type("ELEMWISE") \
+    .async_flag(False) \
+    .binfile_name("relu6_grad.so") \
+    .compute_cost(10) \
+    .kernel_name("relu6_grad") \
+    .partial_flag(True) \
+    .input(0, "gradients", False, "required", "all") \
+    .input(1, "features", False, "required", "all") \
+    .output(0, "backprops", False, "required", "all") \
+    .dtype_format(DataType.F16_5HD, DataType.F16_5HD, DataType.F16_5HD) \
+    .dtype_format(DataType.F16_Default, DataType.F16_Default, DataType.F16_Default) \
+    .dtype_format(DataType.F16_FracNZ, DataType.F16_FracNZ, DataType.F16_FracNZ) \
+    .dtype_format(DataType.F16_C1HWNCoC0, DataType.F16_C1HWNCoC0, DataType.F16_C1HWNCoC0) \
+    .dtype_format(DataType.F32_5HD, DataType.F32_5HD, DataType.F32_5HD) \
+    .dtype_format(DataType.F32_Default, DataType.F32_Default, DataType.F32_Default) \
+    .dtype_format(DataType.F32_FracNZ, DataType.F32_FracNZ, DataType.F32_FracNZ) \
+    .dtype_format(DataType.F32_C1HWNCoC0, DataType.F32_C1HWNCoC0, DataType.F32_C1HWNCoC0) \
+    .get_op_info()
+
+
+@op_info_register(relu6_grad_op_info)
+def _relu6_grad_tbe():
+    """Relu6Grad TBE register"""
+    return