提交 68b39469 authored 作者: amrithasuresh's avatar amrithasuresh

Fixed indentation

上级 2611ec31
...@@ -43,7 +43,7 @@ class BlockSparse_Gemv_and_Outer(utt.InferShapeTester): ...@@ -43,7 +43,7 @@ class BlockSparse_Gemv_and_Outer(utt.InferShapeTester):
input = randn(batchSize, inputWindowSize, inputSize).astype('float32') input = randn(batchSize, inputWindowSize, inputSize).astype('float32')
permutation = np.random.permutation permutation = np.random.permutation
inputIndice = np.vstack(permutation(nInputBlock)[:inputWindowSize] inputIndice = np.vstack(permutation(nInputBlock)[:inputWindowSize]
for _ in range(batchSize)).astype('int32') for _ in range(batchSize)).astype('int32')
outputIndice = np.vstack( outputIndice = np.vstack(
permutation(nOutputBlock)[:outputWindowSize] permutation(nOutputBlock)[:outputWindowSize]
for _ in range(batchSize)).astype('int32') for _ in range(batchSize)).astype('int32')
...@@ -68,9 +68,9 @@ class BlockSparse_Gemv_and_Outer(utt.InferShapeTester): ...@@ -68,9 +68,9 @@ class BlockSparse_Gemv_and_Outer(utt.InferShapeTester):
y = randn(batchSize, yWindowSize, ySize).astype('float32') y = randn(batchSize, yWindowSize, ySize).astype('float32')
randint = np.random.randint randint = np.random.randint
xIdx = np.vstack(randint(0, nInputBlock, size=xWindowSize) xIdx = np.vstack(randint(0, nInputBlock, size=xWindowSize)
for _ in range(batchSize)).astype('int32') for _ in range(batchSize)).astype('int32')
yIdx = np.vstack(randint(0, nOutputBlock, size=yWindowSize) yIdx = np.vstack(randint(0, nOutputBlock, size=yWindowSize)
for _ in range(batchSize)).astype('int32') for _ in range(batchSize)).astype('int32')
return o, x, y, xIdx, yIdx return o, x, y, xIdx, yIdx
...@@ -118,7 +118,7 @@ class BlockSparse_Gemv_and_Outer(utt.InferShapeTester): ...@@ -118,7 +118,7 @@ class BlockSparse_Gemv_and_Outer(utt.InferShapeTester):
for i in range(xIdx.shape[1]): for i in range(xIdx.shape[1]):
for j in range(yIdx.shape[1]): for j in range(yIdx.shape[1]):
o[xIdx[b, i], yIdx[b, j]] += np.outer(x[b, i, :], o[xIdx[b, i], yIdx[b, j]] += np.outer(x[b, i, :],
y[b, j, :]) y[b, j, :])
return o return o
def test_sparseblockdot(self): def test_sparseblockdot(self):
......
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