1 // Copyright 2016 The TensorFlow Authors. All Rights Reserved. 2 // 3 // Licensed under the Apache License, Version 2.0 (the "License"); 4 // you may not use this file except in compliance with the License. 5 // You may obtain a copy of the License at 6 // 7 // http://www.apache.org/licenses/LICENSE-2.0 8 // 9 // Unless required by applicable law or agreed to in writing, software 10 // distributed under the License is distributed on an "AS IS" BASIS, 11 // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 12 // See the License for the specific language governing permissions and 13 // limitations under the License. 14 // ============================================================================= 15 16 #include <limits> 17 18 #include "tensorflow/contrib/ffmpeg/ffmpeg_lib.h" 19 #include "tensorflow/core/framework/common_shape_fns.h" 20 #include "tensorflow/core/framework/op.h" 21 #include "tensorflow/core/framework/op_kernel.h" 22 23 namespace tensorflow { 24 namespace ffmpeg { 25 namespace { 26 27 /* 28 * Encoding implementation, shared across V1 and V2 ops. Creates a new 29 * output in the context. 30 */ 31 void Encode(OpKernelContext* context, const Tensor& contents, 32 const string& file_format, const int32 bits_per_second, 33 const int32 samples_per_second) { 34 std::vector<float> samples; 35 samples.reserve(contents.NumElements()); 36 for (int32 i = 0; i < contents.NumElements(); ++i) { 37 samples.push_back(contents.flat<float>()(i)); 38 } 39 const int32 channel_count = contents.dim_size(1); 40 string encoded_audio; 41 OP_REQUIRES_OK( 42 context, CreateAudioFile(file_format, bits_per_second, samples_per_second, 43 channel_count, samples, &encoded_audio)); 44 45 // Copy the encoded audio file to the output tensor. 46 Tensor* output = nullptr; 47 OP_REQUIRES_OK(context, context->allocate_output(0, TensorShape(), &output)); 48 output->scalar<string>()() = encoded_audio; 49 } 50 51 } // namespace 52 53 /* 54 * Supersedes `EncodeAudioOp`. Allows all parameters to be inputs 55 * instead of attributes, so that the sample rate (and, probably less 56 * usefully, the output file format) can be given as tensors rather than 57 * constants only. 58 */ 59 class EncodeAudioOpV2 : public OpKernel { 60 public: 61 explicit EncodeAudioOpV2(OpKernelConstruction* context) : OpKernel(context) {} 62 63 void Compute(OpKernelContext* context) override { 64 OP_REQUIRES( 65 context, context->num_inputs() == 4, 66 errors::InvalidArgument("EncodeAudio requires exactly four inputs.")); 67 68 const Tensor& contents = context->input(0); 69 const Tensor& file_format_tensor = context->input(1); 70 const Tensor& samples_per_second_tensor = context->input(2); 71 const Tensor& bits_per_second_tensor = context->input(3); 72 73 OP_REQUIRES(context, TensorShapeUtils::IsMatrix(contents.shape()), 74 errors::InvalidArgument( 75 "sampled_audio must be a rank-2 tensor but got shape ", 76 contents.shape().DebugString())); 77 OP_REQUIRES( 78 context, contents.NumElements() <= std::numeric_limits<int32>::max(), 79 errors::InvalidArgument( 80 "sampled_audio cannot have more than 2^31 entries. Shape = ", 81 contents.shape().DebugString())); 82 OP_REQUIRES(context, TensorShapeUtils::IsScalar(file_format_tensor.shape()), 83 errors::InvalidArgument( 84 "file_format must be a rank-0 tensor but got shape ", 85 file_format_tensor.shape().DebugString())); 86 OP_REQUIRES(context, 87 TensorShapeUtils::IsScalar(samples_per_second_tensor.shape()), 88 errors::InvalidArgument( 89 "samples_per_second must be a rank-0 tensor but got shape ", 90 samples_per_second_tensor.shape().DebugString())); 91 OP_REQUIRES(context, 92 TensorShapeUtils::IsScalar(bits_per_second_tensor.shape()), 93 errors::InvalidArgument( 94 "bits_per_second must be a rank-0 tensor but got shape ", 95 bits_per_second_tensor.shape().DebugString())); 96 97 const string file_format = 98 str_util::Lowercase(file_format_tensor.scalar<string>()()); 99 const int32 samples_per_second = 100 samples_per_second_tensor.scalar<int32>()(); 101 const int32 bits_per_second = bits_per_second_tensor.scalar<int32>()(); 102 103 OP_REQUIRES(context, file_format == "wav", 104 errors::InvalidArgument( 105 "file_format must be \"wav\", but got: ", file_format)); 106 OP_REQUIRES(context, samples_per_second > 0, 107 errors::InvalidArgument( 108 "samples_per_second must be positive, but got: ", 109 samples_per_second)); 110 OP_REQUIRES( 111 context, bits_per_second > 0, 112 errors::InvalidArgument("bits_per_second must be positive, but got: ", 113 bits_per_second)); 114 115 Encode(context, contents, file_format, bits_per_second, samples_per_second); 116 } 117 }; 118 119 REGISTER_KERNEL_BUILDER(Name("EncodeAudioV2").Device(DEVICE_CPU), 120 EncodeAudioOpV2); 121 122 REGISTER_OP("EncodeAudioV2") 123 .Input("sampled_audio: float") 124 .Input("file_format: string") 125 .Input("samples_per_second: int32") 126 .Input("bits_per_second: int32") 127 .Output("contents: string") 128 .SetShapeFn(shape_inference::ScalarShape) 129 .Doc(R"doc( 130 Processes a `Tensor` containing sampled audio with the number of channels 131 and length of the audio specified by the dimensions of the `Tensor`. The 132 audio is converted into a string that, when saved to disk, will be equivalent 133 to the audio in the specified audio format. 134 135 The input audio has one row of the tensor for each channel in the audio file. 136 Each channel contains audio samples starting at the beginning of the audio and 137 having `1/samples_per_second` time between them. The output file will contain 138 all of the audio channels contained in the tensor. 139 140 sampled_audio: A rank-2 float tensor containing all tracks of the audio. 141 Dimension 0 is time and dimension 1 is the channel. 142 file_format: A string or rank-0 string tensor describing the audio file 143 format. This value must be `"wav"`. 144 samples_per_second: The number of samples per second that the audio should 145 have, as an int or rank-0 `int32` tensor. This value must be 146 positive. 147 bits_per_second: The approximate bitrate of the encoded audio file, as 148 an int or rank-0 `int32` tensor. This is ignored by the "wav" file 149 format. 150 contents: The binary audio file contents, as a rank-0 string tensor. 151 )doc"); 152 153 /* 154 * Deprecated in favor of EncodeAudioOpV2. 155 */ 156 class EncodeAudioOp : public OpKernel { 157 public: 158 explicit EncodeAudioOp(OpKernelConstruction* context) : OpKernel(context) { 159 OP_REQUIRES_OK(context, context->GetAttr("file_format", &file_format_)); 160 file_format_ = str_util::Lowercase(file_format_); 161 OP_REQUIRES(context, file_format_ == "wav", 162 errors::InvalidArgument("file_format arg must be \"wav\".")); 163 164 OP_REQUIRES_OK( 165 context, context->GetAttr("samples_per_second", &samples_per_second_)); 166 OP_REQUIRES(context, samples_per_second_ > 0, 167 errors::InvalidArgument("samples_per_second must be > 0.")); 168 OP_REQUIRES_OK(context, 169 context->GetAttr("bits_per_second", &bits_per_second_)); 170 } 171 172 void Compute(OpKernelContext* context) override { 173 // Get and verify the input data. 174 OP_REQUIRES( 175 context, context->num_inputs() == 1, 176 errors::InvalidArgument("EncodeAudio requires exactly one input.")); 177 const Tensor& contents = context->input(0); 178 OP_REQUIRES(context, TensorShapeUtils::IsMatrix(contents.shape()), 179 errors::InvalidArgument( 180 "sampled_audio must be a rank 2 tensor but got shape ", 181 contents.shape().DebugString())); 182 OP_REQUIRES( 183 context, contents.NumElements() <= std::numeric_limits<int32>::max(), 184 errors::InvalidArgument( 185 "sampled_audio cannot have more than 2^31 entries. Shape = ", 186 contents.shape().DebugString())); 187 188 Encode(context, contents, file_format_, bits_per_second_, 189 samples_per_second_); 190 } 191 192 private: 193 string file_format_; 194 int32 samples_per_second_; 195 int32 bits_per_second_; 196 }; 197 198 REGISTER_KERNEL_BUILDER(Name("EncodeAudio").Device(DEVICE_CPU), EncodeAudioOp); 199 200 REGISTER_OP("EncodeAudio") 201 .Input("sampled_audio: float") 202 .Output("contents: string") 203 .Attr("file_format: string") 204 .Attr("samples_per_second: int") 205 .Attr("bits_per_second: int = 192000") 206 .SetShapeFn(shape_inference::ScalarShape) 207 .Doc(R"doc( 208 Processes a `Tensor` containing sampled audio with the number of channels 209 and length of the audio specified by the dimensions of the `Tensor`. The 210 audio is converted into a string that, when saved to disk, will be equivalent 211 to the audio in the specified audio format. 212 213 The input audio has one row of the tensor for each channel in the audio file. 214 Each channel contains audio samples starting at the beginning of the audio and 215 having `1/samples_per_second` time between them. The output file will contain 216 all of the audio channels contained in the tensor. 217 218 sampled_audio: A rank 2 tensor containing all tracks of the audio. Dimension 0 219 is time and dimension 1 is the channel. 220 contents: The binary audio file contents. 221 file_format: A string describing the audio file format. This must be "wav". 222 samples_per_second: The number of samples per second that the audio should have. 223 bits_per_second: The approximate bitrate of the encoded audio file. This is 224 ignored by the "wav" file format. 225 )doc"); 226 227 } // namespace ffmpeg 228 } // namespace tensorflow 229
