forked from huawei/mindspore2022
144 lines
4.9 KiB
Python
144 lines
4.9 KiB
Python
import numpy as np
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import pytest
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from mindspore import Tensor, context
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from mindspore.nn import Cell
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import mindspore.ops as ops
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from parallel.utils.utils import compile_net
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input_start_ = Tensor(np.random.normal(size=[8, 8, 8]).astype(np.float32))
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input_end_ = Tensor(np.random.normal(size=[8]).astype(np.float32))
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input_weight_tensor_ = Tensor(np.random.normal(size=[8, 8]).astype(np.float32))
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input_weight_float_ = 0.5
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class Net(Cell):
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def __init__(self, strategy=None):
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super(Net, self).__init__()
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self.lerp = ops.Lerp().shard(strategy)
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def construct(self, *inputs):
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output = self.lerp(*inputs)
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return output
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def test_lerp_auto_parallel_with_weight_tensor():
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"""
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Feature: test Lerp auto parallel
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Description: auto parallel when 'weight' is tensor
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Expectation: compile success
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"""
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context.set_auto_parallel_context(parallel_mode="auto_parallel", device_num=8, global_rank=0)
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net = Net()
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compile_net(net, input_start_, input_end_, input_weight_tensor_)
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def test_lerp_auto_parallel_with_weight_float():
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"""
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Feature: test Lerp auto parallel
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Description: auto parallel when 'weight' is float
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Expectation: compile success
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"""
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context.set_auto_parallel_context(parallel_mode="auto_parallel", device_num=8, global_rank=0)
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net = Net()
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compile_net(net, input_start_, input_end_, input_weight_float_)
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def test_lerp_model_parallel_with_weight_tensor():
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"""
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Feature: test Lerp model parallel
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Description: model parallel when 'weight' is tensor
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Expectation: compile success
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"""
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context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=8, global_rank=0)
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strategy = ((2, 2, 2), (2,), (2, 2))
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net = Net(strategy)
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compile_net(net, input_start_, input_end_, input_weight_tensor_)
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def test_lerp_model_parallel_with_weight_float():
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"""
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Feature: test Lerp model parallel
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Description: model parallel when 'weight' is float
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Expectation: compile success
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"""
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context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=8, global_rank=0)
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strategy = ((2, 2, 2), (2,))
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net = Net(strategy)
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compile_net(net, input_start_, input_end_, input_weight_float_)
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def test_lerp_model_parallel_repeated_cal_with_weight_tensor():
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"""
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Feature: test Lerp model parallel with repeated calculation
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Description: model parallel when 'weight' is tensor
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Expectation: compile success
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"""
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context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=8, global_rank=0)
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strategy = ((1, 2, 2), (2,), (2, 2))
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net = Net(strategy)
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compile_net(net, input_start_, input_end_, input_weight_tensor_)
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def test_lerp_model_parallel_repeated_cal_with_weight_float():
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"""
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Feature: test Lerp model parallel with repeated calculation
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Description: model parallel when 'weight' is float
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Expectation: compile success
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"""
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context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=8, global_rank=0)
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strategy = ((1, 2, 2), (2,))
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net = Net(strategy)
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compile_net(net, input_start_, input_end_, input_weight_float_)
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def test_lerp_data_parallel_with_weight_tensor():
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"""
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Feature: test Lerp data parallel
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Description: data parallel when 'weight' is tensor
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Expectation: compile success
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"""
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context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=8, global_rank=0)
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strategy = ((8, 1, 1), (1,), (1, 1))
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net = Net(strategy)
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compile_net(net, input_start_, input_end_, input_weight_tensor_)
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def test_lerp_data_parallel_with_weight_float():
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"""
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Feature: test Lerp data parallel
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Description: data parallel when 'weight' is float
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Expectation: compile success
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"""
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context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=8, global_rank=0)
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strategy = ((8, 1, 1), (1,))
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net = Net(strategy)
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compile_net(net, input_start_, input_end_, input_weight_float_)
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def test_lerp_strategy_error_with_weight_tensor():
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"""
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Feature: test invalid strategy for Lerp
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Description: illegal strategy when 'weight' is tensor
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Expectation: raise RuntimeError
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"""
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context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=8, global_rank=0)
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strategy = ((4, 2, 1), (1,), (1, 2))
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net = Net(strategy)
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with pytest.raises(RuntimeError):
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compile_net(net, input_start_, input_end_, input_weight_tensor_)
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def test_lerp_strategy_error_with_weight_float():
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"""
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Feature: test invalid strategy for Lerp
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Description: illegal strategy when 'weight' is float
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Expectation: raise RuntimeError
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"""
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context.set_auto_parallel_context(parallel_mode="semi_auto_parallel", device_num=8, global_rank=0)
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strategy = ((4, 1, 2), (1,))
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net = Net(strategy)
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with pytest.raises(RuntimeError):
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compile_net(net, input_start_, input_end_, input_weight_float_)
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