diff options
| -rw-r--r-- | README.md | 37 | ||||
| -rw-r--r-- | tensorflow/core/BUILD | 1 | ||||
| -rw-r--r-- | tensorflow/core/kernels/resize_area_op.cc | 7 | ||||
| -rw-r--r-- | tensorflow/core/kernels/resize_bicubic_op.cc | 7 | ||||
| -rw-r--r-- | tensorflow/core/kernels/resize_bilinear_op.cc | 7 | ||||
| -rw-r--r-- | tensorflow/core/kernels/resize_nearest_neighbor_op.cc | 7 | ||||
| -rw-r--r-- | tensorflow/core/ops/image_ops.cc | 8 | ||||
| -rw-r--r-- | tensorflow/core/ops/ops.pbtxt | 8 | ||||
| -rw-r--r-- | tensorflow/examples/tutorials/word2vec/word2vec_basic.py | 22 | ||||
| -rw-r--r-- | tensorflow/g3doc/api_docs/python/framework.md | 2 | ||||
| -rw-r--r-- | tensorflow/g3doc/resources/dims_types.md | 10 | ||||
| -rw-r--r-- | tensorflow/g3doc/tutorials/deep_cnn/index.md | 2 | ||||
| -rw-r--r-- | tensorflow/python/framework/ops.py | 2 | ||||
| -rw-r--r-- | tensorflow/python/ops/image_ops_test.py | 139 | ||||
| -rw-r--r-- | tensorflow/python/ops/template.py | 2 | ||||
| -rw-r--r-- | tensorflow/python/training/coordinator.py | 8 | ||||
| -rw-r--r-- | tensorflow/stream_executor/BUILD | 1 |
17 files changed, 124 insertions, 146 deletions
@@ -16,11 +16,8 @@ organization for the purposes of conducting machine learning and deep neural networks research. The system is general enough to be applicable in a wide variety of other domains, as well. - -**Note: Currently we do not accept pull requests on github -- see -[CONTRIBUTING.md](CONTRIBUTING.md) for information on how to contribute code -changes to TensorFlow through -[tensorflow.googlesource.com](https://tensorflow.googlesource.com/tensorflow)** +**If you'd like to contribute to tensorflow, be sure to review the [contribution +guidelines](CONTRIBUTING.md).** **We use [github issues](https://github.com/tensorflow/tensorflow/issues) for tracking requests and bugs, but please see @@ -29,35 +26,7 @@ and discussion.** # Download and Setup -To install the CPU version of TensorFlow using a binary package, see the -instructions below. For more detailed installation instructions, including -installing from source, GPU-enabled support, etc., see -[here](tensorflow/g3doc/get_started/os_setup.md). - -## Binary Installation - -The TensorFlow Python API supports Python 2.7 and Python 3.3+. - -The simplest way to install TensorFlow is using -[pip](https://pypi.python.org/pypi/pip) for both Linux and Mac. - -For the GPU-enabled version, or if you encounter installation errors, or for -more detailed installation instructions, see -[here](tensorflow/g3doc/get_started/os_setup.md#detailed_install). - -### Ubuntu/Linux 64-bit - -```bash -# For CPU-only version -$ pip install https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.5.0-cp27-none-linux_x86_64.whl -``` - -### Mac OS X - -```bash -# Only CPU-version is available at the moment. -$ pip install https://storage.googleapis.com/tensorflow/mac/tensorflow-0.5.0-py2-none-any.whl -``` +See [install instructions](tensorflow/g3doc/get_started/os_setup.md). ### Try your first TensorFlow program diff --git a/tensorflow/core/BUILD b/tensorflow/core/BUILD index d2b5e65f12..33444cd45d 100644 --- a/tensorflow/core/BUILD +++ b/tensorflow/core/BUILD @@ -349,6 +349,7 @@ tf_gpu_kernel_library( visibility = ["//visibility:public"], deps = [ ":cuda", + ":framework", "//third_party/eigen3", ], ) diff --git a/tensorflow/core/kernels/resize_area_op.cc b/tensorflow/core/kernels/resize_area_op.cc index 11a6cb1da7..126e50ad73 100644 --- a/tensorflow/core/kernels/resize_area_op.cc +++ b/tensorflow/core/kernels/resize_area_op.cc @@ -144,11 +144,8 @@ class ResizeAreaOp : public OpKernel { .HostMemory("size"), \ ResizeAreaOp<CPUDevice, T>); -REGISTER_KERNEL(uint8); -REGISTER_KERNEL(int8); -REGISTER_KERNEL(int32); -REGISTER_KERNEL(float); -REGISTER_KERNEL(double); +TF_CALL_REAL_NUMBER_TYPES(REGISTER_KERNEL); + #undef REGISTER_KERNEL } // namespace tensorflow diff --git a/tensorflow/core/kernels/resize_bicubic_op.cc b/tensorflow/core/kernels/resize_bicubic_op.cc index ea09c3be0c..83b5af31c5 100644 --- a/tensorflow/core/kernels/resize_bicubic_op.cc +++ b/tensorflow/core/kernels/resize_bicubic_op.cc @@ -131,11 +131,8 @@ class ResizeBicubicOp : public OpKernel { .HostMemory("size"), \ ResizeBicubicOp<CPUDevice, T>); -REGISTER_KERNEL(uint8); -REGISTER_KERNEL(int8); -REGISTER_KERNEL(int32); -REGISTER_KERNEL(float); -REGISTER_KERNEL(double); +TF_CALL_REAL_NUMBER_TYPES(REGISTER_KERNEL); + #undef REGISTER_KERNEL } // namespace tensorflow diff --git a/tensorflow/core/kernels/resize_bilinear_op.cc b/tensorflow/core/kernels/resize_bilinear_op.cc index 1688be42f5..897e3a0f12 100644 --- a/tensorflow/core/kernels/resize_bilinear_op.cc +++ b/tensorflow/core/kernels/resize_bilinear_op.cc @@ -215,11 +215,8 @@ class ResizeBilinearOpGrad : public OpKernel { .HostMemory("size"), \ ResizeBilinearOp<CPUDevice, T>); -REGISTER_KERNEL(uint8); -REGISTER_KERNEL(int8); -REGISTER_KERNEL(int32); -REGISTER_KERNEL(float); -REGISTER_KERNEL(double); +TF_CALL_REAL_NUMBER_TYPES(REGISTER_KERNEL); + #undef REGISTER_KERNEL REGISTER_KERNEL_BUILDER(Name("ResizeBilinearGrad") diff --git a/tensorflow/core/kernels/resize_nearest_neighbor_op.cc b/tensorflow/core/kernels/resize_nearest_neighbor_op.cc index c4eea44044..7f88241a36 100644 --- a/tensorflow/core/kernels/resize_nearest_neighbor_op.cc +++ b/tensorflow/core/kernels/resize_nearest_neighbor_op.cc @@ -178,11 +178,8 @@ class ResizeNearestNeighborOpGrad : public OpKernel { .HostMemory("size"), \ ResizeNearestNeighborOpGrad<CPUDevice, T>); -REGISTER_KERNEL(uint8); -REGISTER_KERNEL(int8); -REGISTER_KERNEL(int32); -REGISTER_KERNEL(float); -REGISTER_KERNEL(double); +TF_CALL_REAL_NUMBER_TYPES(REGISTER_KERNEL); + #undef REGISTER_KERNEL } // namespace tensorflow diff --git a/tensorflow/core/ops/image_ops.cc b/tensorflow/core/ops/image_ops.cc index 51909fe6fc..10464133f9 100644 --- a/tensorflow/core/ops/image_ops.cc +++ b/tensorflow/core/ops/image_ops.cc @@ -22,7 +22,7 @@ REGISTER_OP("ResizeArea") .Input("images: T") .Input("size: int32") .Output("resized_images: float") - .Attr("T: {uint8, int8, int32, float, double}") + .Attr("T: {uint8, int8, int16, int32, int64, float, double}") .Doc(R"doc( Resize `images` to `size` using area interpolation. @@ -40,7 +40,7 @@ REGISTER_OP("ResizeBicubic") .Input("images: T") .Input("size: int32") .Output("resized_images: float") - .Attr("T: {uint8, int8, int32, float, double}") + .Attr("T: {uint8, int8, int16, int32, int64, float, double}") .Doc(R"doc( Resize `images` to `size` using bicubic interpolation. @@ -58,7 +58,7 @@ REGISTER_OP("ResizeBilinear") .Input("images: T") .Input("size: int32") .Output("resized_images: float") - .Attr("T: {uint8, int8, int32, float, double}") + .Attr("T: {uint8, int8, int16, int32, int64, float, double}") .Doc(R"doc( Resize `images` to `size` using bilinear interpolation. @@ -93,7 +93,7 @@ REGISTER_OP("ResizeNearestNeighbor") .Input("images: T") .Input("size: int32") .Output("resized_images: T") - .Attr("T: {uint8, int8, int32, float, double}") + .Attr("T: {uint8, int8, int16, int32, int64, float, double}") .Doc(R"doc( Resize `images` to `size` using nearest neighbor interpolation. diff --git a/tensorflow/core/ops/ops.pbtxt b/tensorflow/core/ops/ops.pbtxt index 761c261dda..b90d6b2ddc 100644 --- a/tensorflow/core/ops/ops.pbtxt +++ b/tensorflow/core/ops/ops.pbtxt @@ -5949,7 +5949,9 @@ op { list { type: DT_UINT8 type: DT_INT8 + type: DT_INT16 type: DT_INT32 + type: DT_INT64 type: DT_FLOAT type: DT_DOUBLE } @@ -5982,7 +5984,9 @@ op { list { type: DT_UINT8 type: DT_INT8 + type: DT_INT16 type: DT_INT32 + type: DT_INT64 type: DT_FLOAT type: DT_DOUBLE } @@ -6015,7 +6019,9 @@ op { list { type: DT_UINT8 type: DT_INT8 + type: DT_INT16 type: DT_INT32 + type: DT_INT64 type: DT_FLOAT type: DT_DOUBLE } @@ -6077,7 +6083,9 @@ op { list { type: DT_UINT8 type: DT_INT8 + type: DT_INT16 type: DT_INT32 + type: DT_INT64 type: DT_FLOAT type: DT_DOUBLE } diff --git a/tensorflow/examples/tutorials/word2vec/word2vec_basic.py b/tensorflow/examples/tutorials/word2vec/word2vec_basic.py index e04e86a100..714d9dccf4 100644 --- a/tensorflow/examples/tutorials/word2vec/word2vec_basic.py +++ b/tensorflow/examples/tutorials/word2vec/word2vec_basic.py @@ -141,16 +141,18 @@ with graph.as_default(): train_labels = tf.placeholder(tf.int32, shape=[batch_size, 1]) valid_dataset = tf.constant(valid_examples, dtype=tf.int32) - # Construct the variables. - embeddings = tf.Variable( - tf.random_uniform([vocabulary_size, embedding_size], -1.0, 1.0)) - nce_weights = tf.Variable( - tf.truncated_normal([vocabulary_size, embedding_size], - stddev=1.0 / math.sqrt(embedding_size))) - nce_biases = tf.Variable(tf.zeros([vocabulary_size])) - - # Look up embeddings for inputs. - embed = tf.nn.embedding_lookup(embeddings, train_inputs) + # Ops and variables pinned to the CPU because of missing GPU implementation + with tf.device('/cpu:0'): + # Look up embeddings for inputs. + embeddings = tf.Variable( + tf.random_uniform([vocabulary_size, embedding_size], -1.0, 1.0)) + embed = tf.nn.embedding_lookup(embeddings, train_inputs) + + # Construct the variables for the NCE loss + nce_weights = tf.Variable( + tf.truncated_normal([vocabulary_size, embedding_size], + stddev=1.0 / math.sqrt(embedding_size))) + nce_biases = tf.Variable(tf.zeros([vocabulary_size])) # Compute the average NCE loss for the batch. # tf.nce_loss automatically draws a new sample of the negative labels each diff --git a/tensorflow/g3doc/api_docs/python/framework.md b/tensorflow/g3doc/api_docs/python/framework.md index 0d572c942e..79d485cc60 100644 --- a/tensorflow/g3doc/api_docs/python/framework.md +++ b/tensorflow/g3doc/api_docs/python/framework.md @@ -1408,7 +1408,7 @@ and Python scalars. For example: ```python import numpy as np -array = np.random.rand((32, 100, 100)) +array = np.random.rand(32, 100, 100) def my_func(arg): arg = tf.convert_to_tensor(arg, dtype=tf.float32) diff --git a/tensorflow/g3doc/resources/dims_types.md b/tensorflow/g3doc/resources/dims_types.md index 875eba6863..c636f8a34a 100644 --- a/tensorflow/g3doc/resources/dims_types.md +++ b/tensorflow/g3doc/resources/dims_types.md @@ -54,14 +54,14 @@ Data type | Python type | Description --- | --- | --- `DT_FLOAT` | `tf.float32` | 32 bits floating point. `DT_DOUBLE` | `tf.float64` | 64 bits floating point. -`DT_INT64` | `tf.int64` | 64 bits signed integer. -`DT_INT32` | `tf.int32` | 32 bits signed integer. -`DT_INT16` | `tf.int16` | 16 bits signed integer. `DT_INT8` | `tf.int8` | 8 bits signed integer. +`DT_INT16` | `tf.int16` | 16 bits signed integer. +`DT_INT32` | `tf.int32` | 32 bits signed integer. +`DT_INT64` | `tf.int64` | 64 bits signed integer. `DT_UINT8` | `tf.uint8` | 8 bits unsigned integer. `DT_STRING` | `tf.string` | Variable length byte arrays. Each element of a Tensor is a byte array. `DT_BOOL` | `tf.bool` | Boolean. `DT_COMPLEX64` | `tf.complex64` | Complex number made of two 32 bits floating points: real and imaginary parts. -`DT_QINT32` | `tf.qint32` | 32 bits signed integer used in quantized Ops. `DT_QINT8` | `tf.qint8` | 8 bits signed integer used in quantized Ops. -`DT_QUINT8` | `tf.quint8` | 8 bits unsigned integer used in quantized Ops. +`DT_QINT32` | `tf.qint32` | 32 bits signed integer used in quantized Ops. +`DT_QUINT8` | `tf.quint8` | 8 bits unsigned integer used in quantized Ops.
\ No newline at end of file diff --git a/tensorflow/g3doc/tutorials/deep_cnn/index.md b/tensorflow/g3doc/tutorials/deep_cnn/index.md index 66614d402f..00d4383f20 100644 --- a/tensorflow/g3doc/tutorials/deep_cnn/index.md +++ b/tensorflow/g3doc/tutorials/deep_cnn/index.md @@ -126,7 +126,7 @@ artificially increase the data set size: * [Randomly flip](../../api_docs/python/image.md#random_flip_left_right) the image from left to right. * Randomly distort the [image brightness](../../api_docs/python/image.md#random_brightness). -* Randomly distort the [image contrast](../../api_docs/python/image.md#tf_image_random_contrast). +* Randomly distort the [image contrast](../../api_docs/python/image.md#random_contrast). Please see the [Images](../../api_docs/python/image.md) page for the list of available distortions. We also attach an diff --git a/tensorflow/python/framework/ops.py b/tensorflow/python/framework/ops.py index ac12551528..d08f98c61c 100644 --- a/tensorflow/python/framework/ops.py +++ b/tensorflow/python/framework/ops.py @@ -486,7 +486,7 @@ def convert_to_tensor(value, dtype=None, name=None, as_ref=False): ```python import numpy as np - array = np.random.rand((32, 100, 100)) + array = np.random.rand(32, 100, 100) def my_func(arg): arg = tf.convert_to_tensor(arg, dtype=tf.float32) diff --git a/tensorflow/python/ops/image_ops_test.py b/tensorflow/python/ops/image_ops_test.py index 3410689864..ad7612d8ab 100644 --- a/tensorflow/python/ops/image_ops_test.py +++ b/tensorflow/python/ops/image_ops_test.py @@ -564,49 +564,56 @@ class ResizeImagesTest(test_util.TensorFlowTestCase): image_ops.ResizeMethod.BICUBIC, image_ops.ResizeMethod.AREA] + TYPES = [np.uint8, np.int8, np.int16, np.int32, np.int64, + np.float, np.double] + def testNoOp(self): img_shape = [1, 6, 4, 1] single_shape = [6, 4, 1] - data = [128, 128, 64, 64, - 128, 128, 64, 64, - 64, 64, 128, 128, - 64, 64, 128, 128, + # This test is also conducted with int8, so 127 is the maximum + # value that can be used. + data = [127, 127, 64, 64, + 127, 127, 64, 64, + 64, 64, 127, 127, + 64, 64, 127, 127, 50, 50, 100, 100, 50, 50, 100, 100] - img_np = np.array(data, dtype=np.uint8).reshape(img_shape) - target_height = 6 target_width = 4 - for opt in self.OPTIONS: - with self.test_session() as sess: - image = constant_op.constant(img_np, shape=img_shape) - y = image_ops.resize_images(image, target_height, target_width, opt) - yshape = array_ops.shape(y) - resized, newshape = sess.run([y, yshape]) - self.assertAllEqual(img_shape, newshape) - self.assertAllClose(resized, img_np, atol=1e-5) + for nptype in self.TYPES: + img_np = np.array(data, dtype=nptype).reshape(img_shape) - # Resizing with a single image must leave the shape unchanged also. - with self.test_session(): - img_single = img_np.reshape(single_shape) - image = constant_op.constant(img_single, shape=single_shape) - y = image_ops.resize_images(image, target_height, target_width, - self.OPTIONS[0]) - yshape = array_ops.shape(y) - newshape = yshape.eval() - self.assertAllEqual(single_shape, newshape) + for opt in self.OPTIONS: + with self.test_session() as sess: + image = constant_op.constant(img_np, shape=img_shape) + y = image_ops.resize_images(image, target_height, target_width, opt) + yshape = array_ops.shape(y) + resized, newshape = sess.run([y, yshape]) + self.assertAllEqual(img_shape, newshape) + self.assertAllClose(resized, img_np, atol=1e-5) - def testResizeDown(self): + # Resizing with a single image must leave the shape unchanged also. + with self.test_session(): + img_single = img_np.reshape(single_shape) + image = constant_op.constant(img_single, shape=single_shape) + y = image_ops.resize_images(image, target_height, target_width, + self.OPTIONS[0]) + yshape = array_ops.shape(y) + newshape = yshape.eval() + self.assertAllEqual(single_shape, newshape) - data = [128, 128, 64, 64, - 128, 128, 64, 64, - 64, 64, 128, 128, - 64, 64, 128, 128, + def testResizeDown(self): + # This test is also conducted with int8, so 127 is the maximum + # value that can be used. + data = [127, 127, 64, 64, + 127, 127, 64, 64, + 64, 64, 127, 127, + 64, 64, 127, 127, 50, 50, 100, 100, 50, 50, 100, 100] - expected_data = [128, 64, - 64, 128, + expected_data = [127, 64, + 64, 127, 50, 100] target_height = 3 target_width = 2 @@ -617,59 +624,61 @@ class ResizeImagesTest(test_util.TensorFlowTestCase): [target_height, target_width, 1]] for target_shape, img_shape in zip(target_shapes, img_shapes): - img_np = np.array(data, dtype=np.uint8).reshape(img_shape) - for opt in self.OPTIONS: - with self.test_session(): - image = constant_op.constant(img_np, shape=img_shape) - y = image_ops.resize_images(image, target_height, target_width, opt) - expected = np.array(expected_data).reshape(target_shape) - resized = y.eval() - self.assertAllClose(resized, expected, atol=1e-5) + for nptype in self.TYPES: + img_np = np.array(data, dtype=nptype).reshape(img_shape) + + for opt in self.OPTIONS: + with self.test_session(): + image = constant_op.constant(img_np, shape=img_shape) + y = image_ops.resize_images(image, target_height, target_width, opt) + expected = np.array(expected_data).reshape(target_shape) + resized = y.eval() + self.assertAllClose(resized, expected, atol=1e-5) def testResizeUp(self): img_shape = [1, 3, 2, 1] - data = [128, 64, - 64, 128, + data = [64, 32, + 32, 64, 50, 100] - img_np = np.array(data, dtype=np.uint8).reshape(img_shape) - target_height = 6 target_width = 4 expected_data = {} expected_data[image_ops.ResizeMethod.BILINEAR] = [ - 128.0, 96.0, 64.0, 64.0, - 96.0, 96.0, 96.0, 96.0, - 64.0, 96.0, 128.0, 128.0, - 57.0, 85.5, 114.0, 114.0, + 64.0, 48.0, 32.0, 32.0, + 48.0, 48.0, 48.0, 48.0, + 32.0, 48.0, 64.0, 64.0, + 41.0, 61.5, 82.0, 82.0, 50.0, 75.0, 100.0, 100.0, 50.0, 75.0, 100.0, 100.0] expected_data[image_ops.ResizeMethod.NEAREST_NEIGHBOR] = [ - 128.0, 128.0, 64.0, 64.0, - 128.0, 128.0, 64.0, 64.0, - 64.0, 64.0, 128.0, 128.0, - 64.0, 64.0, 128.0, 128.0, + 64.0, 64.0, 32.0, 32.0, + 64.0, 64.0, 32.0, 32.0, + 32.0, 32.0, 64.0, 64.0, + 32.0, 32.0, 64.0, 64.0, 50.0, 50.0, 100.0, 100.0, 50.0, 50.0, 100.0, 100.0] expected_data[image_ops.ResizeMethod.AREA] = [ - 128.0, 128.0, 64.0, 64.0, - 128.0, 128.0, 64.0, 64.0, - 64.0, 64.0, 128.0, 128.0, - 64.0, 64.0, 128.0, 128.0, + 64.0, 64.0, 32.0, 32.0, + 64.0, 64.0, 32.0, 32.0, + 32.0, 32.0, 64.0, 64.0, + 32.0, 32.0, 64.0, 64.0, 50.0, 50.0, 100.0, 100.0, 50.0, 50.0, 100.0, 100.0] - for opt in [ - image_ops.ResizeMethod.BILINEAR, - image_ops.ResizeMethod.NEAREST_NEIGHBOR, - image_ops.ResizeMethod.AREA]: - with self.test_session(): - image = constant_op.constant(img_np, shape=img_shape) - y = image_ops.resize_images(image, target_height, target_width, opt) - resized = y.eval() - expected = np.array(expected_data[opt]).reshape( - [1, target_height, target_width, 1]) - self.assertAllClose(resized, expected, atol=1e-05) + for nptype in self.TYPES: + for opt in [ + image_ops.ResizeMethod.BILINEAR, + image_ops.ResizeMethod.NEAREST_NEIGHBOR, + image_ops.ResizeMethod.AREA]: + with self.test_session(): + img_np = np.array(data, dtype=nptype).reshape(img_shape) + image = constant_op.constant(img_np, shape=img_shape) + y = image_ops.resize_images(image, target_height, target_width, opt) + resized = y.eval() + expected = np.array(expected_data[opt]).reshape( + [1, target_height, target_width, 1]) + self.assertAllClose(resized, expected, atol=1e-05) def testResizeUpBicubic(self): img_shape = [1, 6, 6, 1] diff --git a/tensorflow/python/ops/template.py b/tensorflow/python/ops/template.py index 60cff4b97b..78bff9f9db 100644 --- a/tensorflow/python/ops/template.py +++ b/tensorflow/python/ops/template.py @@ -187,7 +187,7 @@ class Template(object): "meant tf.get_variable: %s", variables[vars_at_start:]) return result - except Exception, exc: + except Exception as exc: # Reraise the exception, but append the original definition to the # trace. args = exc.args diff --git a/tensorflow/python/training/coordinator.py b/tensorflow/python/training/coordinator.py index 5030c63370..efd6f2a807 100644 --- a/tensorflow/python/training/coordinator.py +++ b/tensorflow/python/training/coordinator.py @@ -70,7 +70,7 @@ class Coordinator(object): try: while not coord.should_stop(): ...do some work... - except Exception, e: + except Exception as e: coord.request_stop(e) ``` @@ -85,7 +85,7 @@ class Coordinator(object): ...start thread N...(coord, ...) # Wait for all the threads to terminate. coord.join(threads) - except Exception, e: + except Exception as e: ...exception that was passed to coord.request_stop() ``` @@ -188,7 +188,7 @@ class Coordinator(object): ```python try: ...body... - exception Exception, ex: + exception Exception as ex: coord.request_stop(ex) ``` @@ -198,7 +198,7 @@ class Coordinator(object): # pylint: disable=broad-except try: yield - except Exception, ex: + except Exception as ex: self.request_stop(ex) # pylint: enable=broad-except diff --git a/tensorflow/stream_executor/BUILD b/tensorflow/stream_executor/BUILD index cb69c36b75..90186371c3 100644 --- a/tensorflow/stream_executor/BUILD +++ b/tensorflow/stream_executor/BUILD @@ -19,6 +19,7 @@ cc_library( ), hdrs = glob([ "*.h", + "cuda/*.h", "lib/*.h", "platform/**/*.h", ]), |