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Results 11 - 16 of 16 for output_node (0.24 sec)
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tensorflow/compiler/mlir/lite/quantization/lite/quantize_model_test.cc
output_buffer_); EXPECT_THAT(status, Eq(kTfLiteOk)); const Model* output_model = GetModel(output_buffer_.data()); ASSERT_TRUE(output_model); } TEST_P(QuantizeConvModelTest, SkipUnspecifiedLayer) { auto status = QuantizeModel(&model_, TensorType_FLOAT32, TensorType_FLOAT32,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 12 23:15:24 UTC 2024 - 73.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/python/representative_dataset.py
signature_keys=['serving_default'], representative_datasets=dataset_file_map, ) tf.quantization.experimental.quantize_saved_model( '/tmp/input_model', '/tmp/output_model', quantization_options=quantization_options, ) ``` """ def __init__( self, path_map: Mapping[str, os.PathLike[str]],
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Mar 22 22:55:22 UTC 2024 - 14.2K bytes - Viewed (0) -
tensorflow/c/eager/c_api.cc
return ret; } TF_CAPI_EXPORT extern int TFE_OpGetOutputLength(TFE_Op* op, const char* output_name, TF_Status* status) { int ret = -1; status->status = tensorflow::unwrap(op)->OutputLength(output_name, &ret); return ret; } void TFE_Execute(TFE_Op* op, TFE_TensorHandle** retvals, int* num_retvals,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 09 08:11:23 UTC 2024 - 44K bytes - Viewed (0) -
tensorflow/compiler/jit/mark_for_compilation_pass_test.cc
// Nothing should be compiled. EXPECT_EQ(0, clusters.size()); } TEST(XlaCompilationTest, DeterministicClusterNames) { auto create_graph = [](absl::string_view output_name) -> std::unique_ptr<Graph> { std::unique_ptr<Graph> graph(new Graph(OpRegistry::Global())); GraphDefBuilder builder(GraphDefBuilder::kFailImmediately); Tensor t(DT_FLOAT, TensorShape());
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Feb 14 10:11:10 UTC 2024 - 79.6K bytes - Viewed (0) -
tensorflow/c/c_api_test.cc
const auto signature_def = signature_def_map.at("regress_x_to_y"); const string input_name = signature_def.inputs().at(tensorflow::kRegressInputs).name(); const string output_name = signature_def.outputs().at(tensorflow::kRegressOutputs).name(); // Write {0, 1, 2, 3} as tensorflow::Example inputs. Tensor input(tensorflow::DT_STRING, TensorShape({4}));
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Apr 15 03:35:10 UTC 2024 - 96.9K bytes - Viewed (0) -
RELEASE.md
* Added an `output_mode` argument to the `Discretization` and `Hashing` layers with the same semantics as other preprocessing layers. All categorical preprocessing layers now support `output_mode`. * All preprocessing layer output will follow the compute dtype of a `tf.keras.mixed_precision.Policy`, unless constructed with
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 11 23:24:08 UTC 2024 - 730.3K bytes - Viewed (0)