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- # 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.
- # ============================================================================
- import numpy as np
- import pytest
-
- import mindspore as ms
- from mindspore import nn, context, Tensor
- import mindspore.ops as ops
-
- def set_context():
- context.set_context(mode=context.PYNATIVE_MODE)
- context.reset_auto_parallel_context()
- context.set_auto_parallel_context(device_num=8, parallel_mode="auto_parallel", search_mode="sharding_propagation")
-
- class NetMul(nn.Cell):
- def __init__(self):
- super().__init__()
- self.mul = ops.Mul()
-
- def construct(self, x, y):
- return self.mul(x, y)
-
-
- class NetMatMul(nn.Cell):
- def __init__(self):
- super().__init__()
- self.matmul = ops.MatMul()
-
- def construct(self, x, y):
- return self.matmul(x, y)
-
- class Net(nn.Cell):
- def __init__(self, in_axes, out_axes):
- super().__init__()
- self.mul_net = NetMul()
- self.matmul_net = NetMatMul()
- self.mul_net.shard(in_axes=in_axes, out_axes=out_axes)
-
- def construct(self, x, y):
- out1 = self.matmul_net(x, y)
- out2 = self.matmul_net(x, y)
- return self.mul_net(out1, out2)
-
- def cell_shard_execution(in_axes, out_axes, error_log):
-
- net = Net(in_axes, out_axes)
-
- x = Tensor(np.ones([128, 128]), dtype=ms.float32)
- y = Tensor(np.ones([128, 128]), dtype=ms.float32)
-
- with pytest.raises(Exception) as err:
- _ = net(x, y)
- assert error_log in str(err.value)
-
-
- def test_in_axes_numbers_check():
- """
- Feature: shard function for cell
- Description: inconsistent input number and in_axes number
- Expectation: throw an exception indicating inconsistent input number and in_axes number
- """
- set_context()
- in_axes = ((8, 1), None, (1, 8))
- out_axes = (None,)
- error_log = "Input numbers: 2 is not equal to in_axes numbers: 3"
- cell_shard_execution(in_axes, out_axes, error_log)
-
-
- def test_out_axes_numbers_check():
- """
- Feature: shard function for cell
- Description: inconsistent output number and out_axes number
- Expectation: throw an exception indicating inconsistent output number and out_axes number
- """
- set_context()
- in_axes = ((8, 1), None)
- out_axes = (None, (8, 1))
- error_log = "Output number: 1 is not equal to out_axes number: 2"
- cell_shard_execution(in_axes, out_axes, error_log)
-
- def test_in_axes_dimension_check():
- """
- Feature: shard function for cell
- Description: inconsistent input dimension and in_axes dimension
- Expectation: throw an exception indicating inconsistent input_dimension and in_axes dimension
- """
- set_context()
- in_axes = ((8, 1, 1), None)
- out_axes = (None, (8, 1))
- error_log = "Input dimension: 2 is not equal to in_axes dimension: 3 at index 0"
- cell_shard_execution(in_axes, out_axes, error_log)
-
- def test_out_axes_dimension_check():
- """
- Feature: shard function for cell
- Description: inconsistent output dimension and out_axes dimension
- Expectation: throw an exception indicating inconsistent output_dimension and out_axes dimension
- """
- set_context()
- in_axes = ((8, 1), None)
- out_axes = ((8,),)
- error_log = "Output dimension: 2 is not equal to out_axes dimension: 1 at index 0"
- cell_shard_execution(in_axes, out_axes, error_log)
-
- def test_in_axes_format_check():
- """
- Feature: shard function for cell
- Description: unsupported in_axes format
- Expectation: throw an exception indicating an supported in_axes format
- """
- set_context()
- in_axes = ([8, 1], None)
- out_axes = (None,)
- error_log = "in_axes should be a two-dimension tuple"
- cell_shard_execution(in_axes, out_axes, error_log)
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