Make all the image decode ops handle all formats

Too many users try to decode pngs as jpegs.  Now, if you pass a png to
decode_jpeg, or a gif to decode_png, it silently does what the user was
expecting.

Unfortunately, tf.image.decode_image still exists as a separate thing in
Python, since decode_gif returns 4-D shapes incompatible with the other ops.  A
future CL could clean that up, but it's hard to do in a backwards compatible
way.  As is, decode_png and decode_jpeg will bail if you try to decode an
animated gif, and produce 3-D images for nonanimated gifs.

Also fix some crash-on-error bugs and memory leak bugs in gif_io.cc.

RELNOTES: Make decode_jpeg/decode_png/decode_gif handle all formats, since users frequently try to decode an image as the wrong type.

Fixes #9786.

PiperOrigin-RevId: 155888493

1 files changed, 0 insertions, 118 deletions

diff --git a/tensorflow/core/kernels/decode_png_op.cc b/tensorflow/core/kernels/decode_png_op.cc
deleted file mode 100644
index 1906ae7746..0000000000
--- a/tensorflow/core/kernels/decode_png_op.cc
+++ /dev/null
@@ -1,118 +0,0 @@
-/* Copyright 2015 The TensorFlow Authors. All Rights Reserved.
-
-Licensed under the Apache License, Version 2.0 (the "License");
-you may not use this file except in compliance with the License.
-You may obtain a copy of the License at
-
-    http://www.apache.org/licenses/LICENSE-2.0
-
-Unless required by applicable law or agreed to in writing, software
-distributed under the License is distributed on an "AS IS" BASIS,
-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-See the License for the specific language governing permissions and
-limitations under the License.
-==============================================================================*/
-
-// See docs in ../ops/image_ops.cc
-
-#include <memory>
-#include "tensorflow/core/framework/op_kernel.h"
-#include "tensorflow/core/framework/register_types.h"
-#include "tensorflow/core/framework/tensor.h"
-#include "tensorflow/core/framework/tensor_shape.h"
-#include "tensorflow/core/framework/types.h"
-#include "tensorflow/core/framework/types.pb.h"
-#include "tensorflow/core/lib/core/status.h"
-#include "tensorflow/core/lib/png/png_io.h"
-#include "tensorflow/core/platform/logging.h"
-
-namespace tensorflow {
-
-// Decode the contents of a PNG file
-class DecodePngOp : public OpKernel {
- public:
-  explicit DecodePngOp(OpKernelConstruction* context) : OpKernel(context) {
-    OP_REQUIRES_OK(context, context->GetAttr("channels", &channels_));
-    OP_REQUIRES(context, channels_ == 0 || channels_ == 1 || channels_ == 3 ||
-                             channels_ == 4,
-                errors::InvalidArgument("channels must be 0, 1, 3, or 4, got ",
-                                        channels_));
-
-    DataType dt;
-    OP_REQUIRES_OK(context, context->GetAttr("dtype", &dt));
-    OP_REQUIRES(
-        context, dt == DataType::DT_UINT8 || dt == DataType::DT_UINT16,
-        errors::InvalidArgument("Type must be UINT8 or UINT16, got ", dt));
-    if (dt == DataType::DT_UINT8) {
-      desired_channel_bits_ = 8;
-    } else {
-      desired_channel_bits_ = 16;
-    }
-  }
-
-  void Compute(OpKernelContext* context) override {
-    const Tensor& contents = context->input(0);
-    OP_REQUIRES(context, TensorShapeUtils::IsScalar(contents.shape()),
-                errors::InvalidArgument("contents must be scalar, got shape ",
-                                        contents.shape().DebugString()));
-
-    // Start decoding image to get shape details
-    const StringPiece data = contents.scalar<string>()();
-    png::DecodeContext decode;
-    OP_REQUIRES(
-        context,
-        png::CommonInitDecode(data, channels_, desired_channel_bits_, &decode),
-        errors::InvalidArgument("Invalid PNG header, data size ", data.size()));
-
-    // Verify that width and height are not too large:
-    // - verify width and height don't overflow int.
-    // - width can later be multiplied by channels_ and sizeof(uint16), so
-    //   verify single dimension is not too large.
-    // - verify when width and height are multiplied together, there are a few
-    //   bits to spare as well.
-    const int width = static_cast<int>(decode.width);
-    const int height = static_cast<int>(decode.height);
-    const int64 total_size =
-        static_cast<int64>(width) * static_cast<int64>(height);
-    if (width != static_cast<int64>(decode.width) || width <= 0 ||
-        width >= (1LL << 27) || height != static_cast<int64>(decode.height) ||
-        height <= 0 || height >= (1LL << 27) || total_size >= (1LL << 29)) {
-      png::CommonFreeDecode(&decode);
-      OP_REQUIRES(context, false,
-                  errors::InvalidArgument("PNG size too large for int: ",
-                                          decode.width, " by ", decode.height));
-    }
-
-    // Allocate tensor
-    Tensor* output = nullptr;
-    const auto status = context->allocate_output(
-        0, TensorShape({height, width, decode.channels}), &output);
-    if (!status.ok()) png::CommonFreeDecode(&decode);
-    OP_REQUIRES_OK(context, status);
-
-    if (desired_channel_bits_ == 8) {
-      // Finish decoding image
-      OP_REQUIRES(
-          context,
-          png::CommonFinishDecode(
-              reinterpret_cast<png_bytep>(output->flat<uint8>().data()),
-              decode.channels * width * sizeof(uint8), &decode),
-          errors::InvalidArgument("Invalid PNG data, size ", data.size()));
-    } else {
-      // Finish decoding image
-      OP_REQUIRES(
-          context,
-          png::CommonFinishDecode(
-              reinterpret_cast<png_bytep>(output->flat<uint16>().data()),
-              decode.channels * width * sizeof(uint16), &decode),
-          errors::InvalidArgument("Invalid PNG data, size ", data.size()));
-    }
-  }
-
- private:
-  int channels_;
-  int desired_channel_bits_;
-};
-REGISTER_KERNEL_BUILDER(Name("DecodePng").Device(DEVICE_CPU), DecodePngOp);
-
-}  // namespace tensorflow