forked from mindspore-Ecosystem/mindspore
psnr check two input same shape and type
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@ -95,6 +95,11 @@ def _gauss_kernel_helper(filter_size):
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g = Tensor(g)
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return filter_size, g
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@constexpr
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def _check_input_4d(input_shape, param_name, func_name):
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if len(input_shape) != 4:
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raise ValueError(f"{func_name} {param_name} should be 4d, but got shape {input_shape}")
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return True
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class SSIM(Cell):
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r"""
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@ -146,6 +151,9 @@ class SSIM(Cell):
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self.mean = P.DepthwiseConv2dNative(channel_multiplier=1, kernel_size=filter_size)
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def construct(self, img1, img2):
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_check_input_4d(F.shape(img1), "img1", "SSIM")
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_check_input_4d(F.shape(img2), "img2", "SSIM")
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P.SameTypeShape()(img1, img2)
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max_val = _convert_img_dtype_to_float32(self.max_val, self.max_val)
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img1 = _convert_img_dtype_to_float32(img1, self.max_val)
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img2 = _convert_img_dtype_to_float32(img2, self.max_val)
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@ -236,6 +244,9 @@ class PSNR(Cell):
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self.max_val = max_val
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def construct(self, img1, img2):
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_check_input_4d(F.shape(img1), "img1", "PSNR")
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_check_input_4d(F.shape(img2), "img2", "PSNR")
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P.SameTypeShape()(img1, img2)
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max_val = _convert_img_dtype_to_float32(self.max_val, self.max_val)
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img1 = _convert_img_dtype_to_float32(img1, self.max_val)
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img2 = _convert_img_dtype_to_float32(img2, self.max_val)
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@ -18,10 +18,12 @@ test psnr
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import numpy as np
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import pytest
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import mindspore.nn as nn
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from mindspore.common import dtype as mstype
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from mindspore.common.api import _executor
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from mindspore import Tensor
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class PSNRNet(nn.Cell):
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def __init__(self, max_val=1.0):
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super(PSNRNet, self).__init__()
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@ -59,3 +61,38 @@ def test_psnr_max_val_zero():
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max_val = 0
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with pytest.raises(ValueError):
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net = PSNRNet(max_val)
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def test_psnr_different_shape():
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shape_1 = (8, 3, 16, 16)
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shape_2 = (8, 3, 8, 8)
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img1 = Tensor(np.random.random(shape_1))
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img2 = Tensor(np.random.random(shape_2))
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net = PSNRNet()
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with pytest.raises(ValueError):
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_executor.compile(net, img1, img2)
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def test_psnr_different_dtype():
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dtype_1 = mstype.float32
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dtype_2 = mstype.float16
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img1 = Tensor(np.random.random((8, 3, 16, 16)), dtype=dtype_1)
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img2 = Tensor(np.random.random((8, 3, 16, 16)), dtype=dtype_2)
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net = PSNRNet()
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with pytest.raises(TypeError):
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_executor.compile(net, img1, img2)
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def test_psnr_invalid_5d_input():
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shape_1 = (8, 3, 16, 16)
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shape_2 = (8, 3, 8, 8)
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invalid_shape = (8, 3, 16, 16, 1)
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img1 = Tensor(np.random.random(shape_1))
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invalid_img1 = Tensor(np.random.random(invalid_shape))
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img2 = Tensor(np.random.random(shape_2))
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invalid_img2 = Tensor(np.random.random(invalid_shape))
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net = PSNRNet()
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with pytest.raises(ValueError):
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_executor.compile(net, invalid_img1, img2)
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with pytest.raises(ValueError):
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_executor.compile(net, img1, invalid_img2)
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with pytest.raises(ValueError):
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_executor.compile(net, invalid_img1, invalid_img2)
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@ -18,6 +18,7 @@ test ssim
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import numpy as np
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import pytest
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import mindspore.nn as nn
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import mindspore.common.dtype as mstype
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from mindspore.common.api import _executor
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from mindspore import Tensor
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@ -93,3 +94,38 @@ def test_ssim_k1_k2_wrong_value():
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net = SSIMNet(k2=0.0)
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with pytest.raises(ValueError):
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net = SSIMNet(k2=-1.0)
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def test_ssim_different_shape():
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shape_1 = (8, 3, 16, 16)
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shape_2 = (8, 3, 8, 8)
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img1 = Tensor(np.random.random(shape_1))
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img2 = Tensor(np.random.random(shape_2))
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net = SSIMNet()
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with pytest.raises(ValueError):
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_executor.compile(net, img1, img2)
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def test_ssim_different_dtype():
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dtype_1 = mstype.float32
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dtype_2 = mstype.float16
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img1 = Tensor(np.random.random((8, 3, 16, 16)), dtype=dtype_1)
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img2 = Tensor(np.random.random((8, 3, 16, 16)), dtype=dtype_2)
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net = SSIMNet()
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with pytest.raises(TypeError):
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_executor.compile(net, img1, img2)
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def test_ssim_invalid_5d_input():
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shape_1 = (8, 3, 16, 16)
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shape_2 = (8, 3, 8, 8)
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invalid_shape = (8, 3, 16, 16, 1)
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img1 = Tensor(np.random.random(shape_1))
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invalid_img1 = Tensor(np.random.random(invalid_shape))
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img2 = Tensor(np.random.random(shape_2))
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invalid_img2 = Tensor(np.random.random(invalid_shape))
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net = SSIMNet()
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with pytest.raises(ValueError):
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_executor.compile(net, invalid_img1, img2)
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with pytest.raises(ValueError):
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_executor.compile(net, img1, invalid_img2)
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with pytest.raises(ValueError):
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_executor.compile(net, invalid_img1, invalid_img2)
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