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Results 11 - 13 of 13 for _output_shapes (0.18 sec)
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tensorflow/compiler/mlir/tensorflow/transforms/tf_passes.td
%arg1: tensor<i64> ) { %1 = "tf.ReduceDataset"(%arg0, %arg1) { Targuments = [], Tstate = [i64], device = "", f = @__reduce_func_1, f._tf_data_function = true, output_shapes = [#tf_type.shape<>], output_types = [i64], use_inter_op_parallelism = true, _xla_compile_device_type="TPU"} : (tensor<!tf_type.variant>, tensor<i64>) -> (tensor<i64>) func.return } ```
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 12 21:18:05 UTC 2024 - 99.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/ir/tfl_ops.td
let summary = "Transpose convolution operator"; let description = [{ Performs transpose convolution operation on input. }]; let arguments = (ins TFL_I32Tensor:$output_shape, TFL_TensorOf<[F32, QI8, QUI8, QI16]>:$weights, TFL_TensorOf<[F32, QI8, QUI8, QI16]>:$input, TFL_TensorOfOrNone<[F32, QI32, I64]>:$bias, TFL_PaddingAttr:$padding,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jun 06 19:09:08 UTC 2024 - 186K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/ir/tf_ops_n_z.cc
IsWithinInt32Range); if (elements_all_in_int32_range) { std::vector<int32_t> output_shape(output_ty.getRank()); std::transform(output_ty.getShape().begin(), output_ty.getShape().end(), output_shape.begin(), [](int64_t val) { return static_cast<int32_t>(val); }); output_int_type = tensorflow::GetTypeFromTFTensorShape(
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 09 22:07:10 UTC 2024 - 170.8K bytes - Viewed (0)