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tensorflow/c/eager/unified_api_testutil.h
absl::Span<AbstractTensorHandle*> outputs, bool use_function); Status BuildImmediateExecutionContext(bool use_tfrt, AbstractContext** ctx); // Return a tensor handle with given type, values and dimensions. template <class T, TF_DataType datatype> Status TestTensorHandleWithDims(AbstractContext* ctx, const T* data, const int64_t* dims, int num_dims,
C - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Tue Feb 27 13:57:45 GMT 2024 - 4K bytes - Viewed (0) -
tensorflow/c/experimental/grappler/grappler.h
TF_Bool include_output_tensor_values, TF_Status* s); // Get the size of input OpInfo::TensorProperties given node name. TF_CAPI_EXPORT extern void TF_GetInputPropertiesListSize( TF_GraphProperties* graph_properties, const char* name, int* num_values, TF_Status* status); // Get the size of output OpInfo::TensorProperties given node name. TF_CAPI_EXPORT extern void TF_GetOutputPropertiesListSize(
C - Registered: Tue Feb 27 12:39:08 GMT 2024 - Last Modified: Wed Aug 03 18:08:43 GMT 2022 - 12.5K bytes - Viewed (0) -
CITATION.cff
given-names: Lukasz - family-names: Kudlur given-names: Manjunath - family-names: Levenberg given-names: Josh - family-names: Mané given-names: Dan - family-names: Schuster given-names: Mike - family-names: Monga given-names: Rajat - family-names: Moore given-names: Sherry - family-names: Murray given-names: Derek - family-names: Olah given-names: Chris
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tensorflow/c/experimental/gradients/math_grad.cc
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tensorflow/c/eager/abstract_operation.h
// Sets the operation device name. // // The given `name` must be parseable by DeviceNameUtils::ParseFullName, and // the result will be used as a constraint for device placement. See the // documentation for DeviceName for more details. // // The value will override the previous value - that is, no "merging" of // existing and given constraints will be performed. virtual Status SetDeviceName(const char* name) = 0;
C - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Wed Jul 14 16:20:41 GMT 2021 - 6.8K bytes - Viewed (0) -
ci/official/containers/linux_arm64/setup.packages.sh
# See the License for the specific language governing permissions and # limitations under the License. # ============================================================================== # # setup.packages.sh: Given a list of Ubuntu packages, install them and clean up. # Usage: setup.packages.sh <package_list.txt> set -e # Prevent apt install tzinfo from asking our location (assumes UTC) export DEBIAN_FRONTEND=noninteractive
Shell Script - Registered: Tue Apr 30 12:39:09 GMT 2024 - Last Modified: Fri Sep 29 00:26:34 GMT 2023 - 1.1K bytes - Viewed (0) -
tensorflow/c/eager/gradient_checker.h
#include "tensorflow/c/eager/abstract_tensor_handle.h" #include "tensorflow/c/eager/unified_api_testutil.h" namespace tensorflow { namespace gradients { /* Returns numerical grad inside `dtheta_approx` given `forward` model and * parameter specified by `input_index`. * * I.e. if y = <output of the forward model> and w = inputs[input_index], * this will calculate dy/dw numerically. *
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.github/bot_config.yml
Apparently, your CPU model does not support AVX instruction sets. You can still use TensorFlow with the alternatives given below: * Try Google Colab to use TensorFlow.
Others - Registered: Tue May 07 12:40:20 GMT 2024 - Last Modified: Tue Oct 17 11:48:07 GMT 2023 - 4K bytes - Viewed (0) -
ci/official/requirements_updater/README.md
dependencies are always used. \ See https://github.com/bazelbuild/rules_python/ for more details. ### Specifying the Python version Note: Only a number of minor Python versions are supported at any given time. By default, the lowest supported version is used. To set a different version, use the `TF_PYTHON_VERSION` environment variable, e.g. ``` export TF_PYTHON_VERSION=3.11 ```
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tensorflow/c/experimental/gradients/nn_grad.cc
Status Compute(AbstractContext* ctx, absl::Span<AbstractTensorHandle* const> grad_outputs, absl::Span<AbstractTensorHandle*> grad_inputs) override { /* Given upstream grad U and a BiasAdd: A + bias, the gradients are: * * dA = U * dbias = reduceSum(U, dims = channel_dim) */ AbstractTensorHandle* upstream_grad = grad_outputs[0];
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