!1121 Complete vm ops for ResizeBilinear and ResizeBilinearGrad

Merge pull request !1121 from lihongkang/master

mindspore/ccsrc/kernel/tbe/tbe_adapter.cc

@@ -78,6 +78,8 @@ static std::map<string, string> tbe_func_adapter_map = {
   {"pad", "pad_d"},
   {"space_to_batch", "space_to_batch_d"},
   {"batch_to_space", "batch_to_space_d"},
+  {"resize_bilinear", "resize_bilinear_v2_d"},
+  {"resize_bilinear_grad", "resize_bilinear_v2_grad"},
   {"adam", "apply_adam_d"}};
 
 void TbeAdapter::NormalizeFuncName(std::string *func_name) {

mindspore/ops/_op_impl/tbe/__init__.py

@@ -162,3 +162,5 @@ from .batch_to_space import _batch_to_space_tbe
 from .space_to_batch import _space_to_batch_tbe
 from .floor import _floor_tbe
 from .log1p import _log1p_tbe
+from .resize_bilinear import _resize_bilinear_tbe
+from .resize_bilinear_grad import _resize_bilinear_grad_tbe

mindspore/ops/_op_impl/tbe/resize_bilinear.py

@@ -0,0 +1,39 @@
+# 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.
+# ============================================================================
+
+"""ResizeBilinear op"""
+from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
+
+resize_bilinear_op_info = TBERegOp("ResizeBilinear") \
+    .fusion_type("OPAQUE") \
+    .async_flag(False) \
+    .binfile_name("resize_bilinear_v2_d.so") \
+    .compute_cost(10) \
+    .kernel_name("resize_bilinear_v2_d") \
+    .partial_flag(True) \
+    .attr("size", "required", "listInt", "all") \
+    .attr("align_corners", "optional", "bool", "all") \
+    .attr("half_pixel_centers", "optional", "bool", "all") \
+    .input(0, "x", False, "required", "all") \
+    .output(0, "y", False, "required", "all") \
+    .dtype_format(DataType.F16_5HD, DataType.F32_5HD) \
+    .dtype_format(DataType.F32_5HD, DataType.F32_5HD) \
+    .get_op_info()
+
+
+@op_info_register(resize_bilinear_op_info)
+def _resize_bilinear_tbe():
+    """ResizeBilinear TBE register"""
+    return

mindspore/ops/_op_impl/tbe/resize_bilinear_grad.py

@@ -0,0 +1,38 @@
+# 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.
+# ============================================================================
+
+"""ResizeBilinearGrad op"""
+from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
+
+resize_bilinear_grad_op_info = TBERegOp("ResizeBilinearGrad") \
+    .fusion_type("OPAQUE") \
+    .async_flag(False) \
+    .binfile_name("resize_bilinear_v2_grad.so") \
+    .compute_cost(10) \
+    .kernel_name("resize_bilinear_v2_grad") \
+    .partial_flag(True) \
+    .attr("align_corners", "optional", "bool", "all") \
+    .attr("half_pixel_centers", "optional", "bool", "all")\
+    .input(0, "grads", False, "required", "all") \
+    .input(1, "original_image", False, "required", "all") \
+    .output(0, "y", False, "required", "all") \
+    .dtype_format(DataType.F32_5HD, DataType.F32_5HD, DataType.F32_5HD) \
+    .get_op_info()
+
+
+@op_info_register(resize_bilinear_grad_op_info)
+def _resize_bilinear_grad_tbe():
+    """ResizeBilinearGrad TBE register"""
+    return

tests/ut/python/ops/test_ops.py

@@ -924,6 +924,15 @@ test_case_nn_ops = [
         'block': P.L2Loss(),
         'desc_inputs': [Tensor(np.array([[1, 1], [2, 2], [3, 3], [4, 4]]), mstype.float16)],
         'desc_bprop': []}),
+    ('ResizeBilinear', {
+        'block': P.ResizeBilinear((5, 5)),
+        'desc_inputs': [Tensor([[[[1, 2, 3, 4, 5], [1, 2, 3, 4, 5]]]], mstype.float16)],
+        'desc_bprop': [Tensor([[[[1, 2, 3, 4, 5], [1, 2, 3, 4, 5]]]], mstype.float16)]}),
+    ('ResizeBilinearGrad', {
+        'block': G.ResizeBilinearGrad(),
+        'desc_inputs': [Tensor([[[[1, 2, 3, 4, 5]]]], mstype.float32), Tensor([[[[1, 2, 3, 4, 5]]]], mstype.float32)],
+        'desc_bprop': [Tensor([[[[1, 2, 3, 4, 5]]]], mstype.float32)],
+        'skip': ['backward']}),
 ]
 
 test_case_array_ops = [