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Fix coo layers

This commit is contained in:
huangxinjing 2021-11-12 16:06:02 +08:00
parent 95f0c98747
commit 8c2dec7fe2
2 changed files with 7 additions and 12 deletions
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2
mindspore/ccsrc/frontend/parallel/step_parallel.cc
View File

@ -2974,7 +2974,7 @@ CommInfo GetCommInfo() {
!ParallelContext::GetInstance()->hccl_test_available()) {
// hccl_test_available is used when we compile graphs in real ascend card environment, but with hccl_test.
MS_LOG(EXCEPTION) << "The device_num " << device_num << " set in the context is not consist with "
<< world_rank_size << " devices you have "
<< world_rank_size << " devices you have"
<< ". Please check your rank_table file(for Ascend) or host file(for GPU).";
}
#endif

17
mindspore/parallel/nn/layers.py
View File

@ -338,14 +338,10 @@ class _Linear(Cell):
raise TypeError(f"param type should in [float32, float16], but found type {type(param_init_type)}")
if activation and not isinstance(activation, str):
raise ValueError("Activation can only be str, but found type {}".format(activation))
if isinstance(weight_init, Tensor):
if weight_init.ndim != 2 or weight_init.shape[0] != out_channels or \
weight_init.shape[1] != in_channels:
raise ValueError("Weight init shape error.")
if transpose_b:
weight_shape = [out_channels, in_channels]
else:
weight_shape = [in_channels, out_channels]
if isinstance(weight_init, Tensor) and (weight_init.ndim != 2 or weight_init.shape[0] != out_channels or \
weight_init.shape[1] != in_channels):
raise ValueError("Weight init shape error.")
weight_shape = [out_channels, in_channels] if transpose_b else [in_channels, out_channels]
self.expert_num = expert_num
if self.expert_num > 1:
self.expert_flag = True
@ -359,9 +355,8 @@ class _Linear(Cell):
self.bias = None
self.has_bias = has_bias
if self.has_bias:
if isinstance(bias_init, Tensor):
if bias_init.ndim != 1 or bias_init.shape[0] != out_channels:
raise ValueError("Bias init shape error.")
if isinstance(bias_init, Tensor) and (bias_init.ndim != 1 or bias_init.shape[0] != out_channels):
raise ValueError("Bias init shape error.")
self.bias = Parameter(initializer(bias_init, [out_channels], param_init_type), name="bias")
self.bias_add = P.Add()
self.act_name = activation