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ci/official/wheel_test/README.md
"tf.foo" being imported first. The `_api/v2/api_packages.txt` file is generated during the TensorFlow API v2 init files creation process and is subsequently stored in the wheel file after the build. It also contains a few paths that cannot be directly imported. These paths point to attributes or sub-modules within a module's namespace, but they don't correspond to an actual file or directory on the filesystem. The list of
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tensorflow/c/c_api_test.cc
TEST(CAPI, ShapeInferenceError) { // TF_FinishOperation should fail if the shape of the added operation cannot // be inferred. TF_Status* status = TF_NewStatus(); TF_Graph* graph = TF_NewGraph(); // Create this failure by trying to add two nodes with incompatible shapes // (A tensor with shape [2] and a tensor with shape [3] cannot be added). const char data[] = {1, 2, 3}; const int64_t vec2_dims[] = {2};
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tensorflow/c/experimental/filesystem/modular_filesystem_test.cc
if (fs == nullptr || !s.ok()) GTEST_SKIP() << "No filesystem registered: " << s; s = fs->CreateDir(root_dir_); if (!s.ok()) { GTEST_SKIP() << "Cannot create working directory: " << s; } } // Converts path reference to URI reference. // // If URI scheme is empty, URI reference is `path` relative to current test
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tensorflow/c/eager/c_api_test.cc
} else { // In sync mode, forwarding can't really happen since the client code will // have a reference count on the input tensor while the kernel is being // executed and thus it cannot be re-used for the return tensor. EXPECT_NE(orig_ptr, TF_TensorData(t)); } } ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status); TFE_DeleteTensorHandle(m);
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tensorflow/c/c_api.cc
status->status = tensorflow::errors::OutOfRange( "Cannot update edge. Input index [", dst.index, "] is greater than the number of total inputs [", ic_dst->num_inputs(), "]."); return; } if (!ic_dst->MergeInput(dst.index, shape)) { status->status = tensorflow::errors::InvalidArgument( "Cannot update edge, incompatible shapes: ", ic_dst->DebugString(shape),
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ci/official/README.md
# Ex. py311 -- Python 3.11 # Ex. py312 -- Python 3.12 # 2. Choose the platform, which corresponds to the version of TensorFlow to # build. This should also match the system you're using--you cannot build # the TF MacOS package from Linux. # Ex. linux_x86 -- x86_64 Linux platform # Ex. linux_x86_cuda -- x86_64 Linux platform, with Nvidia CUDA support # Ex. macos_arm64 -- arm64 MacOS platform
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CONTRIBUTING.md
- Once the PR is in the Google codebase, we make sure it integrates well with its dependencies and the rest of the system. - Rarely, If the tests fail at this stage, we cannot merge the code. - If needed, we may come to you to make some changes. At times, it may not be you, it may be us who may have hit a snag. Please be patient while we work to fix this.
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ci/official/containers/linux_arm64/builder.devtoolset/build_devtoolset.sh
cp "./aarch64-unknown-linux-gnu/libstdc++-v3/src/.libs/libstdc++_nonshared44.a" \ "${TARGET}/usr/lib64" # Link in architecture specific includes from the system; note that we cannot # link in the whole aarch64-linux-gnu folder, as otherwise we're overlaying # system gcc paths that we do not want to find. # TODO(klimek): Automate linking in all non-gcc / non-kernel include # directories.
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tensorflow/c/experimental/filesystem/modular_filesystem_registration.cc
// // If the numbers don't match, plugin cannot be loaded. static Status CheckABI(int pluginABI, int coreABI, StringPiece where) { if (pluginABI != coreABI) return errors::FailedPrecondition( strings::StrCat("Plugin ABI (", pluginABI, ") for ", where, " operations doesn't match expected core ABI (", coreABI, "). Plugin cannot be loaded.")); return OkStatus(); }
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tensorflow/c/eager/gradients.h
// Unwatches this tensor on the tape. Mainly used for cleanup when deleting // eager tensors. void DeleteTrace(const AbstractTensorHandle*); // Consumes the internal state of the tape (so cannot be called more than // once unless the tape is persistent) and produces the gradient of the target // tensors with respect to the source tensors. The output gradients are used
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