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| author |  A. Unique TensorFlower <gardener@tensorflow.org> | 2018-01-30 10:43:03 -0800 |
|---|---|---|
| committer | TensorFlower Gardener <gardener@tensorflow.org> | 2018-01-30 12:33:54 -0800 |
| commit | 4463d105a8a4a83642b9709ba79310e8f4ddf577 (patch) | |
| tree | 240e9a0a9a6b9ad956c704776a33126ba00cbfe8 /tensorflow/contrib/image | |
| parent | 8f0e7207774279f4fe50f4d6c4fbd576e2941463 (diff) | |
Cleanup: Ran clang-format on all *.{cc,h} files in tensorflow/contrib/.../*.{hh,c}.
PiperOrigin-RevId: 183855242
Diffstat (limited to 'tensorflow/contrib/image')
3 files changed, 12 insertions, 9 deletions
diff --git a/tensorflow/contrib/image/kernels/image_ops.cc b/tensorflow/contrib/image/kernels/image_ops.cc index 6adf837ca0..c2e32da133 100644 --- a/tensorflow/contrib/image/kernels/image_ops.cc +++ b/tensorflow/contrib/image/kernels/image_ops.cc @@ -43,9 +43,9 @@ template struct FillProjectiveTransform<CPUDevice, double>; typedef Eigen::ThreadPoolDevice CPUDevice; using functor::FillProjectiveTransform; +using generator::Interpolation; using generator::INTERPOLATION_BILINEAR; using generator::INTERPOLATION_NEAREST; -using generator::Interpolation; using generator::ProjectiveGenerator; template <typename Device, typename T> @@ -72,11 +72,12 @@ class ImageProjectiveTransform : public OpKernel { const Tensor& transform_t = ctx->input(1); OP_REQUIRES(ctx, images_t.shape().dims() == 4, errors::InvalidArgument("Input images must have rank 4")); - OP_REQUIRES(ctx, (TensorShapeUtils::IsMatrix(transform_t.shape()) && - (transform_t.dim_size(0) == images_t.dim_size(0) || - transform_t.dim_size(0) == 1) && - transform_t.dim_size(1) == - ProjectiveGenerator<Device, T>::kNumParameters), + OP_REQUIRES(ctx, + (TensorShapeUtils::IsMatrix(transform_t.shape()) && + (transform_t.dim_size(0) == images_t.dim_size(0) || + transform_t.dim_size(0) == 1) && + transform_t.dim_size(1) == + ProjectiveGenerator<Device, T>::kNumParameters), errors::InvalidArgument( "Input transform should be num_images x 8 or 1 x 8")); auto images = images_t.tensor<T, 4>(); diff --git a/tensorflow/contrib/image/kernels/single_image_random_dot_stereograms_ops.cc b/tensorflow/contrib/image/kernels/single_image_random_dot_stereograms_ops.cc index 9f0bf37aed..8f9a5c2803 100755 --- a/tensorflow/contrib/image/kernels/single_image_random_dot_stereograms_ops.cc +++ b/tensorflow/contrib/image/kernels/single_image_random_dot_stereograms_ops.cc @@ -143,8 +143,8 @@ class SingleImageRandomDotStereogramsOp : public OpKernel { } data_box_left = deltaX_border_image / 2; // Center DATA in X dimension - data_box_width = data_Xwindow; // width of scan line - data_box_height = data_Ywindow; // hight of image + data_box_width = data_Xwindow; // width of scan line + data_box_height = data_Ywindow; // hight of image const T* inputZ = input_tensor.flat<T>().data(); // Flatten input Z buffer diff --git a/tensorflow/contrib/image/ops/single_image_random_dot_stereograms_ops.cc b/tensorflow/contrib/image/ops/single_image_random_dot_stereograms_ops.cc index 1f41f243f2..8139d4272d 100755 --- a/tensorflow/contrib/image/ops/single_image_random_dot_stereograms_ops.cc +++ b/tensorflow/contrib/image/ops/single_image_random_dot_stereograms_ops.cc @@ -58,7 +58,9 @@ REGISTER_OP("SingleImageRandomDotStereograms") int colors; TF_RETURN_IF_ERROR(c->GetAttr("number_colors", &colors)); - c->set_output(0, c->MakeShape({y_dim, x_dim, colors > 256? c->MakeDim(3) : c->MakeDim(1)})); + c->set_output( + 0, c->MakeShape( + {y_dim, x_dim, colors > 256 ? c->MakeDim(3) : c->MakeDim(1)})); return Status::OK(); }) .Doc(R"doc( |