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Results 1 - 3 of 3 for op_kernel (0.16 sec)
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tensorflow/c/c_api.cc
#include "tensorflow/core/framework/kernel_def.pb.h" #include "tensorflow/core/framework/log_memory.h" #include "tensorflow/core/framework/node_def_util.h" #include "tensorflow/core/framework/op_kernel.h" #include "tensorflow/core/framework/partial_tensor_shape.h" #include "tensorflow/core/framework/shape_inference.h" #include "tensorflow/core/framework/tensor.h" #include "tensorflow/core/framework/tensor.pb.h" // NOLINT
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Apr 15 03:35:10 UTC 2024 - 102.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/transforms/legalize_hlo.cc
"multiplier"); } // Slicing with dynamic offsets (helper method advised) auto create_slice = [&](mlir::Value tensor, int depth_idx, int channel_idx, bool is_kernel = false) -> mlir::Value { std::vector<int64_t> tensor_shape = mlir::cast<ShapedType>(tensor.getType()).getShape().vec(); // Calculate offsets based on depth_idx, channel_idx and tensor_shape
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 154.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/python/integration_test/quantize_model_test.py
y_shape = [v if v is not None else n for v in shapes[1]] class MatmulModel(module.Module): def __init__(self, bias: Optional[core.Tensor]): self._bias = bias self._kernel = np.random.uniform(size=y_shape).astype('f4') self._min = (-0.8, -0.8, -0.9) self._max = (0.9, 0.9, 1.0) @def_function.function( input_signature=[
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 17 03:36:50 UTC 2024 - 235.6K bytes - Viewed (0)