!1242 support vm for Argmax

Merge pull request !1242 from jiangjinsheng/vm_arg_max

mindspore/ccsrc/kernel/tbe/tbe_adapter.cc

@@ -77,6 +77,7 @@ static std::map<string, string> tbe_func_adapter_map = {
   {"resize_nearest_neighbor", "resize_nearest_neighbor_v2_d"},
   {"resize_nearest_neighbor_grad", "resize_nearest_neighbor_v2_grad_d"},
   {"pad", "pad_d"},
+  {"argmax", "arg_max_d"},
   {"space_to_batch", "space_to_batch_d"},
   {"batch_to_space", "batch_to_space_d"},
   {"resize_bilinear", "resize_bilinear_v2_d"},

mindspore/ops/_op_impl/tbe/__init__.py

@@ -175,6 +175,7 @@ from .bounding_box_decode import _bounding_box_decode_tbe
 from .bounding_box_encode import _bounding_box_encode_tbe
 from .check_valid import _check_valid_tbe
 from .iou import _iou_tbe
+from .arg_max import _arg_max_tbe
 from .nms_with_mask import nms_with_mask_op_info
 from .random_choice_with_mask import random_choice_with_mask_op_info
 from .sgd import sgd_op_info

mindspore/ops/_op_impl/tbe/arg_max.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.
+# ============================================================================
+
+"""Argmax op"""
+from mindspore.ops.op_info_register import op_info_register, TBERegOp, DataType
+
+arg_max_op_info = TBERegOp("Argmax") \
+    .fusion_type("ELEMWISE") \
+    .async_flag(False) \
+    .binfile_name("arg_max_d.so") \
+    .compute_cost(10) \
+    .kernel_name("arg_max_d") \
+    .partial_flag(True) \
+    .attr("axis", "required", "int", "all") \
+    .attr("output_dtype", "optional", "type", "all") \
+    .input(0, "x", False, "required", "all") \
+    .output(0, "y", False, "required", "all") \
+    .dtype_format(DataType.F16_Default, DataType.I32_Default) \
+    .dtype_format(DataType.F32_Default, DataType.I32_Default) \
+    .get_op_info()
+
+
+@op_info_register(arg_max_op_info)
+def _arg_max_tbe():
+    """Argmax TBE register"""
+    return

mindspore/ops/operations/array_ops.py

@@ -951,8 +951,8 @@ class Argmax(PrimitiveWithInfer):
 
     Args:
         axis (int): Axis on which Argmax operation applies. Default: -1.
-        output_type (:class:`mindspore.dtype`): An optional data type of `mindspore.dtype.int32` and
+        output_type (:class:`mindspore.dtype`): An optional data type of `mindspore.dtype.int32`.
-            `mindspore.dtype.int64`. Default: `mindspore.dtype.int64`.
+            Default: `mindspore.dtype.int32`.
 
     Inputs:
         - **input_x** (Tensor) - Input tensor.
@@ -961,12 +961,12 @@ class Argmax(PrimitiveWithInfer):
         Tensor, indices of the max value of input tensor across the axis.
 
     Examples:
-        >>> input_x = Tensor(np.array([2.0, 3.1, 1.2]))
+        >>> input_x = Tensor(np.array([2.0, 3.1, 1.2]), mindspore.float32)
         >>> index = P.Argmax(output_type=mindspore.int32)(input_x)
     """
 
     @prim_attr_register
-    def __init__(self, axis=-1, output_type=mstype.int64):
+    def __init__(self, axis=-1, output_type=mstype.int32):
         """init Argmax"""
         self.init_prim_io_names(inputs=['x'], outputs=['output'])
         validator.check_value_type("axis", axis, [int], self.name)