From 6d5c580a61b92e368342dbffc547798b6b2df5b5 Mon Sep 17 00:00:00 2001 From: buxue Date: Thu, 16 Jul 2020 19:44:24 +0800 Subject: [PATCH] change shape and dtype of tensor from interface to attr --- mindspore/nn/graph_kernels/graph_kernels.py | 2 +- mindspore/nn/layer/quant.py | 6 +++--- model_zoo/gat/src/gat.py | 6 +++--- tests/st/pynative/test_ops.py | 2 +- 4 files changed, 8 insertions(+), 8 deletions(-) diff --git a/mindspore/nn/graph_kernels/graph_kernels.py b/mindspore/nn/graph_kernels/graph_kernels.py index 21cc4f87109..21a4c38ac5b 100644 --- a/mindspore/nn/graph_kernels/graph_kernels.py +++ b/mindspore/nn/graph_kernels/graph_kernels.py @@ -1020,7 +1020,7 @@ class LayerNorm(Cell): Examples: >>> x = Tensor(np.ones([20, 5, 10, 10]), mindspore.float32) - >>> shape1 = x.shape()[1:] + >>> shape1 = x.shape[1:] >>> m = G.LayerNorm(shape1, begin_norm_axis=1, begin_params_axis=1) >>> m(x) """ diff --git a/mindspore/nn/layer/quant.py b/mindspore/nn/layer/quant.py index 63cdedbfe94..2f4f2032904 100644 --- a/mindspore/nn/layer/quant.py +++ b/mindspore/nn/layer/quant.py @@ -746,8 +746,8 @@ class DenseQuant(Cell): self.has_bias = check_bool(has_bias) if isinstance(weight_init, Tensor): - if weight_init.dim() != 2 or weight_init.shape()[0] != out_channels or \ - weight_init.shape()[1] != in_channels: + if weight_init.dim() != 2 or weight_init.shape[0] != out_channels or \ + weight_init.shape[1] != in_channels: raise ValueError("weight_init shape error") self.weight = Parameter(initializer( @@ -755,7 +755,7 @@ class DenseQuant(Cell): if self.has_bias: if isinstance(bias_init, Tensor): - if bias_init.dim() != 1 or bias_init.shape()[0] != out_channels: + if bias_init.dim() != 1 or bias_init.shape[0] != out_channels: raise ValueError("bias_init shape error") self.bias = Parameter(initializer( diff --git a/model_zoo/gat/src/gat.py b/model_zoo/gat/src/gat.py index 3cb3cc11066..ff0c964e9b7 100644 --- a/model_zoo/gat/src/gat.py +++ b/model_zoo/gat/src/gat.py @@ -77,15 +77,15 @@ class GNNFeatureTransform(nn.Cell): self.has_bias = check_bool(has_bias) if isinstance(weight_init, Tensor): - if weight_init.dim() != 2 or weight_init.shape()[0] != out_channels or \ - weight_init.shape()[1] != in_channels: + if weight_init.dim() != 2 or weight_init.shape[0] != out_channels or \ + weight_init.shape[1] != in_channels: raise ValueError("weight_init shape error") self.weight = Parameter(initializer(weight_init, [out_channels, in_channels]), name="weight") if self.has_bias: if isinstance(bias_init, Tensor): - if bias_init.dim() != 1 or bias_init.shape()[0] != out_channels: + if bias_init.dim() != 1 or bias_init.shape[0] != out_channels: raise ValueError("bias_init shape error") self.bias = Parameter(initializer(bias_init, [out_channels]), name="bias") diff --git a/tests/st/pynative/test_ops.py b/tests/st/pynative/test_ops.py index 3cec24fb10c..c43e626be5e 100644 --- a/tests/st/pynative/test_ops.py +++ b/tests/st/pynative/test_ops.py @@ -28,4 +28,4 @@ def test_cast(): type_dst = ms.float32 cast = P.Cast() result = cast(input_x, type_dst) - assert result.dtype() == type_dst + assert result.dtype == type_dst