| /external/tensorflow/tensorflow/tools/lib_package/ |
| LibTensorFlowTest.java | 1 /* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
18 import org.tensorflow.TensorFlow;
22 System.out.println(TensorFlow.version());
|
| /external/tensorflow/tensorflow/java/src/test/java/org/tensorflow/ |
| TensorFlowTest.java | 1 /* Copyright 2016 The TensorFlow Authors. All Rights Reserved.
16 package org.tensorflow;
25 /** Unit tests for {@link org.tensorflow.TensorFlow}. */
30 assertTrue(TensorFlow.version().length() > 0);
35 // Would be nice to actually parse the output as a tensorflow.OpList protocol buffer message,
38 assertTrue(TensorFlow.registeredOpList().length > 0);
55 byte[] opList = TensorFlow.loadLibrary("tensorflow/java/my_test_op.so");
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| /external/tensorflow/tensorflow/java/src/main/java/org/tensorflow/ |
| TensorFlow.java | 1 /* Copyright 2016 The TensorFlow Authors. All Rights Reserved.
16 package org.tensorflow;
18 /** Static utility methods describing the TensorFlow runtime. */
19 public final class TensorFlow {
20 /** Returns the version of the underlying TensorFlow runtime. */
24 * All the TensorFlow operations available in this address space.
27 * href="https://www.tensorflow.org/code/tensorflow/core/framework/op_def.proto">OpList</a>
28 * protocol buffer, which lists all the available TensorFlow operations.
38 * href="https://www.tensorflow.org/code/tensorflow/core/framework/op_def.proto">OpList</a
[all...] |
| SavedModelBundle.java | 1 /* Copyright 2016 The TensorFlow Authors. All Rights Reserved.
16 package org.tensorflow;
24 * href="https://www.tensorflow.org/code/tensorflow/core/protobuf/meta_graph.proto">MetaGraphDef
31 * using the <a href="https://www.tensorflow.org/api_docs/python/tf/saved_model">Saved Model
44 * href="https://www.tensorflow.org/code/tensorflow/core/protobuf/meta_graph.proto">MetaGraphDef
101 TensorFlow.init();
|
| DataType.java | 1 /* Copyright 2016 The TensorFlow Authors. All Rights Reserved.
16 package org.tensorflow;
20 import org.tensorflow.types.UInt8;
39 * <p>TensorFlow uses the STRING type for an arbitrary sequence of bytes.
51 // The integer value must match the corresponding TF_* value in the TensorFlow C API.
56 /** Corresponding value of the TF_DataType enum in the TensorFlow C API. */
71 "DataType " + c + " is not recognized in Java (version " + TensorFlow.version() + ")");
77 * @param c The class describing the TensorFlow type of interest.
79 * @throws IllegalArgumentException if objects of {@code c} do not correspond to a TensorFlow
86 c.getName() + " objects cannot be used as elements in a TensorFlow Tensor")
[all...] |
| Graph.java | 1 /* Copyright 2016 The TensorFlow Authors. All Rights Reserved.
16 package org.tensorflow;
21 * A data flow graph representing a TensorFlow computation.
105 * Import a serialized representation of a TensorFlow graph.
118 * Import a serialized representation of a TensorFlow graph.
120 * @param graphDef the serialized representation of a TensorFlow graph.
258 TensorFlow.init();
|
| NativeLibrary.java | 1 /* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
16 package org.tensorflow;
24 * Helper class for loading the TensorFlow Java native library.
26 * <p>The Java TensorFlow bindings require a native (JNI) library. This library
38 * set of ClassLoader resources (under org/tensorflow/native/OS-ARCH). The resources paths used for
39 * lookup must be consistent with any packaging (such as on Maven Central) of the TensorFlow Java
44 System.getProperty("org.tensorflow.NativeLibrary.DEBUG") != null;
53 // that has already been loaded. For example, tensorflow/examples/android and
54 // tensorflow/contrib/android include the required native code in differently named libraries.
78 "Cannot find TensorFlow native library for OS: %s, architecture: %s. See
[all...] |
| /external/tensorflow/tensorflow/core/common_runtime/sycl/ |
| sycl_device_context.h | 1 /* Copyright 2016 The TensorFlow Authors. All Rights Reserved.
17 #error This file must only be included when building TensorFlow with SYCL support
23 #include "tensorflow/core/common_runtime/device.h"
24 #include "tensorflow/core/framework/device_base.h"
26 namespace tensorflow { namespace
43 } // namespace tensorflow
|
| sycl_allocator.h | 1 /* Copyright 2016 The TensorFlow Authors. All Rights Reserved.
17 #error This file must only be included when building TensorFlow with SYCL support
24 #include "tensorflow/core/framework/allocator.h"
25 #include "tensorflow/core/platform/mutex.h"
26 #include "tensorflow/core/platform/types.h"
28 namespace tensorflow { namespace
73 } // namespace tensorflow
|
| sycl_util.h | 1 /* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
17 #error This file must only be included when building TensorFlow with SYCL support
24 #include "tensorflow/core/common_runtime/device.h"
26 #include "tensorflow/core/common_runtime/dma_helper.h"
27 #include "tensorflow/core/framework/tensor.h"
29 namespace tensorflow { namespace
78 } // namespace tensorflow
|
| sycl_device.h | 1 /* Copyright 2016 The TensorFlow Authors. All Rights Reserved.
17 #error This file must only be included when building TensorFlow with SYCL support
23 #include "tensorflow/core/common_runtime/local_device.h"
24 #include "tensorflow/core/common_runtime/sycl/sycl_allocator.h"
25 #include "tensorflow/core/common_runtime/sycl/sycl_device_context.h"
26 #include "tensorflow/core/public/session_options.h"
28 namespace tensorflow { namespace
230 } // namespace tensorflow
|
| /external/tensorflow/tensorflow/c/ |
| generate-pc.sh | 2 # Copyright 2017 The TensorFlow Authors. All Rights Reserved.
22 echo -e "-v, --version\tset TensorFlow version"
53 echo "Generating pkgconfig file for TensorFlow $TF_VERSION in $TF_PREFIX"
55 cat << EOF > tensorflow.pc
61 Name: TensorFlow
|
| /external/tensorflow/tensorflow/contrib/mpi/ |
| README.md | 1 ## How to compile and use MPI-enabled TensorFlow
5 ```Do you wish to build TensorFlow with MPI support [y/N]```
13 By using this protocol TensorFlow can take advantage of the high performance networking primitives that are offered via the MPI API. This enables TensorFlow to take advantage of high performance low latency networks such as Infiniband. These changes are largely transparent to the user who only has to change the offered protocol and launch the script using the 'mpirun' launcher. For example:
48 The implementation takes over the responsibility for sending and receiving tensors between separate processes. This is facilitated by TensorFlow's ability to support different protocols. In this particular implementation, the standard gRPC library is used for all administrative operations while the MPI functions take over the tensor exchanges. On the sending side the tensors are placed in the standard waiting tables and nothing is changed there. On the receiving side the RecvFromRemoteAsync function is newly implemented and instead of requesting the data via gRPC the data is now requested via MPI calls.
56 Once a request has arrived from a remote process the request is forwarded to the original TensorFlow code which looks up the tensor in the waiting table. Once the tensor has been found a callback is executed which places the found tensor on the sendQueue for the MPI thread. Once the sendQueue is served the tensor data will be send using non-blocking send operations (MP_Isend) to the remote process.
59 The MPI thread will check if there are any incoming tensor request messages on the communication lines using MPI_Iprobe. Once a request has been received it will be passed on to the standard TensorFlow code and eventually will be placed on the sendQueue.
66 The MPI processes identify each other using an MPI process ID. The TensorFlow gRPC processes identify each other using a name. During launch we create a mapping between the TensorFlow process name and the MPI process ID to allow the processes to communicate with the correct destinations when using MPI operations.
|
| /external/tensorflow/tensorflow/go/ |
| android.go | 1 // Copyright 2016 The TensorFlow Authors. All Rights Reserved.
17 package tensorflow package
|
| /external/tensorflow/tensorflow/core/profiler/g3doc/ |
| profile_model_architecture.md | 9 `VariableV2` operation type might contain variables created by TensorFlow
48 * It must have `RegisterStatistics('flops')` defined in TensorFlow. tfprof
|
| options.md | 10 TensorFlow graph node.
12 TensorFlow graph node.
13 * code view. Tree. Each profiler node includes to all TensorFlow
15 * op view. List. Each profiler node includes to all TensorFlow
103 `-account_type_regexes`: Account and display the nodes whose types match one of the type regexes specified. tfprof allow user to define extra operation types for graph nodes through tensorflow.tfprof.OpLogProto proto. regexes are comma-sperated.
|
| profile_time.md | 3 * [Times in TensorFlow and tfprof](#times-in-tensorflow-and-tfprof)
10 ### Times in TensorFlow and tfprof
11 When we run a model, Tensorflow schedules and runs the nodes (operations)
17 by TensorFlow on CPU. Normally, it's the code in OpKernel::Compute.
83 # You can also dive deeper into tensorflow's libraries.
|
| command_line.md | 45 tensorflow.tfprof.OpLogProto (optional). A proto used to provide extra operation
55 <b>--checkpoint_path:</b> TensorFlow checkpoint (optional).
66 bazel build --config opt tensorflow/core/profiler:profiler
69 bazel-bin/tensorflow/core/profiler/profiler help
80 bazel-bin/tensorflow/core/profiler/profiler \
91 bazel-bin/tensorflow/core/profiler/profiler \
96 bazel-bin/tensorflow/core/profiler/profiler \
100 bazel-bin/tensorflow/core/profiler/profiler \
106 bazel-bin/tensorflow/core/profiler/profiler \
114 bazel-bin/tensorflow/core/profiler/profiler
[all...] |
| /external/tensorflow/tensorflow/contrib/verbs/ |
| README.md | 1 ## How to compile, use and configure RDMA-enabled TensorFlow
4 ```Do you wish to build TensorFlow with VERBS-RDMA support [y/N]```
23 The design is based on TensorFlow r1.0. An RDMA path is added between servers for tensor transfer (weights, gradients, etc). The existing GRPC path remains and is responsible for "administrative" tasks, such as setting up the RDMA path, exchanging computation graphs, etc.
25 During the server setup, an RDMA manager is created to manage low-level RDMA components such as RDMA channel and RDMA adapter, an RDMA rendezvous manager is created to oversee send/recv operations between servers. Following the distributed TensorFlow design philosophy, the send operation is passive, i.e. merely placing a tensor in the local out-going table. It is the receive operation that actually initiates the tensor transfer.
27 TensorFlow dynamically allocates memory for tensors that are to be sent or received. This causes difficulty for RDMA operations where pinned memory is required. Few remedies are possible:
30 3. Following HKUST research on the use of GPU direct, and their [GDR implementation](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/contrib/gdr/README.md), there is a smart way to benefit from the TensorFlow allocation theme which is mostly pool based, i.e allocators pre-allocate a large memory block, and allocate the tensors from there. By attaching a custom Visitor to relevant allocators, we can do a single registration of the entire memory block, which zeros the registration overhead. Once the block is registered, each new tensor allocated will be at a registered address, which will allow us to do direct RDMA writes to it.
55 The tensor transfer process is initiated when the receiver requests a tensor. In code it is done by calling **Rendezvous::Recv()** or **Rendezvous::RecvAsync()**. The TensorFlow base implementation handles the case where the requested tensor is located on the same node. The m (…)
[all...] |
| /external/tensorflow/tensorflow/contrib/makefile/ |
| README.md | 0 ### TensorFlow Makefile
3 The recommended way to build TensorFlow from source is using the Bazel
26 You will compile tensorflow and protobuf libraries that you can link into other
32 First, clone this TensorFlow repository.
38 tensorflow/contrib/makefile/download_dependencies.sh
42 like Eigen in the `tensorflow/contrib/makefile/downloads/` folder.
44 You should download the example graph from [https://storage.googleapis.com/download.tensorflow.org/models/inception5h.zip](https://storage.googleapis.com/download.tensorflow.org/models/inception5h.zip).
58 tensorflow/contrib/makefile/build_all_linux.sh
62 `tensorflow/contrib/makefile/gen/lib/libtensorflow-core.a`
[all...] |
| /external/tensorflow/tensorflow/java/src/main/java/org/tensorflow/examples/ |
| LabelImage.java | 1 /* Copyright 2016 The TensorFlow Authors. All Rights Reserved.
16 package org.tensorflow.examples;
26 import org.tensorflow.DataType;
27 import org.tensorflow.Graph;
28 import org.tensorflow.Output;
29 import org.tensorflow.Session;
30 import org.tensorflow.Tensor;
31 import org.tensorflow.TensorFlow;
32 import org.tensorflow.types.UInt8
[all...] |
| /external/tensorflow/tensorflow/contrib/android/java/org/tensorflow/contrib/android/ |
| TensorFlowInferenceInterface.java | 1 /* Copyright 2016 The TensorFlow Authors. All Rights Reserved.
16 package org.tensorflow.contrib.android;
34 import org.tensorflow.Graph;
35 import org.tensorflow.Operation;
36 import org.tensorflow.Session;
37 import org.tensorflow.Tensor;
38 import org.tensorflow.TensorFlow;
39 import org.tensorflow.Tensors;
40 import org.tensorflow.types.UInt8
[all...] |
| /external/tensorflow/tensorflow/contrib/lite/models/testdata/g3doc/ |
| README.md | 3 Sample test data has been provided for speech related models in Tensorflow Lite
17 version of TensorFlow Lite.
96 are generated by running the equivalent TensorFlow model by feeding them the
104 rank=1)](https://storage.googleapis.com/download.tensorflow.org/models/tflite/speech_hotword_model_rank1_2017_11_14.tflite)
107 rank=2)](https://storage.googleapis.com/download.tensorflow.org/models/tflite/speech_hotword_model_rank2_2017_11_14.tflite)
110 model](https://storage.googleapis.com/download.tensorflow.org/models/tflite/speech_speakerid_model_2017_11_14.tflite)
113 model](https://storage.googleapis.com/download.tensorflow.org/models/tflite/speech_tts_model_2017_11_14.tflite)
116 model](https://storage.googleapis.com/download.tensorflow.org/models/tflite/speech_terse_am_model_2017_11_14.tflite)
121 test](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/lite/models/speech_hotword_model_test.cc
[all...] |
| /external/tensorflow/tensorflow/contrib/lite/tools/ |
| visualize.py | 2 # Copyright 2017 The TensorFlow Authors. All Rights Reserved.
16 """This tool creates an html visualization of a TensorFlow Lite graph.
32 _SCHEMA = "third_party/tensorflow/contrib/lite/schema/schema.fbs"
314 html += "<h1>TensorFlow Lite Model</h2>"
|
| /external/tensorflow/tensorflow/core/kernels/ |
| cwise_ops_sycl_common.h | 1 /* Copyright 2016 The TensorFlow Authors. All Rights Reserved.
17 #error This file must only be included when building TensorFlow with SYCL support
25 #include "tensorflow/core/framework/register_types.h"
26 #include "tensorflow/core/kernels/cwise_ops.h"
27 #include "tensorflow/core/platform/types.h"
29 namespace tensorflow { namespace
161 } // end namespace tensorflow
|
