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Results 91 - 100 of 120 for _output_shapes (0.35 sec)
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tensorflow/compiler/mlir/tensorflow/tests/order_by_dialect.mlir
return %arg0 : tensor<!tf_type.variant> } // CHECK-LABEL: iterators func.func private @iterators(%arg0 : tensor<!tf_type.variant>) { %0 = "tf.Iterator"() {container = "", output_shapes = [#tf_type.shape<200x28x28x1>, #tf_type.shape<200x10>], output_types = [f32, f32], shared_name = "_iterator1"} : () -> tensor<!tf_type.resource> %1 = func.call @id(%arg0) : (tensor<!tf_type.variant>) -> tensor<!tf_type.variant>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Apr 06 15:32:52 UTC 2024 - 7.6K bytes - Viewed (0) -
tensorflow/cc/gradients/math_grad.cc
// n_input_entries/n_output_entries // = group_size auto input_shape = Shape(scope, op.input(0)); auto output_shape = Shape(scope, op.output(0)); auto zero = Const(scope, 0); auto group_size = SafeDivHelper(scope, Prod(scope, input_shape, zero), Prod(scope, output_shape, zero)); // propagate sum_grad/group_size grad_outputs->push_back(
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Aug 25 18:20:20 UTC 2023 - 50.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/quantize_weights.mlir
"tf.While"(%cst_0, %cst, %cst_0, %arg0, %cst_1) {T = [i32, i32, i32, f32, f32],_lower_using_switch_merge = true, _num_original_outputs = 5 : i64, _read_only_resource_inputs = [], body = @while_body, cond = @while_cond, device = "", is_stateless = true, output_shapes = [#tf_type.shape<>, #tf_type.shape<>, #tf_type.shape<>, #tf_type.shape<1x1024>, #tf_type.shape<1024x1024>], parallel_iterations = 10 : i64, shape_invariant} : (tensor<i32>, tensor<i32>, tensor<i32>, tensor<1x1024xf32>, tensor<1024x1024xf32>) ->...
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 42K bytes - Viewed (0) -
tensorflow/compiler/jit/xla_launch_util.cc
const xla::HloInputOutputAliasConfig& input_output_alias, absl::Span<const int> input_mapping, const std::map<int, const Tensor*>& resource_vars_snapshots, DataType output_dtype, const TensorShape& output_shape, Allocator* output_allocator, bool allocate_xla_tensors, se::Stream* stream, bool use_multiple_streams, std::shared_ptr<se::Event> definition_event) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 16 00:36:08 UTC 2024 - 40.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/utils/convert_tensor.cc
return ConvertTensor(t, builder); } void ConvertToTensorShapeProto(ArrayRef<int64_t> shape, TensorShapeProto* output_shape) { for (auto d : shape) { output_shape->add_dim()->set_size(ShapedType::isDynamic(d) ? kTFDynamicSize : d); } }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Apr 26 09:37:10 UTC 2024 - 20.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/quantize.mlir
%output_shape = arith.constant dense<[2, 3, 2, 2048]> : tensor<4xi32> %f16_weights = "tfl.pseudo_const"() {value = dense<1.0> : tensor<4x2x2x2048xf16>} : () -> tensor<4x2x2x2048xf16> %dq_weights = "tfl.dequantize"(%f16_weights) : (tensor<4x2x2x2048xf16>) -> tensor<4x2x2x2048xf32> %bias = "tfl.no_value"() {value} : () -> none
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 28 23:10:13 UTC 2024 - 39.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/split_into_island_per_op.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 20.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/breakup-islands.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Oct 31 08:59:10 UTC 2023 - 28.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/shape_inference.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jan 23 17:24:10 UTC 2024 - 167.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/transforms/legalize_hlo.cc
} auto output_shape = mlir::cast<RankedTensorType>(conv_op.getResult().getType()) .getShape(); SmallVector<int64_t, 4> transposed_output_shape = { output_shape[dnums.getOutputBatchDimension()], output_shape[dnums.getOutputSpatialDimensions().data()[0]], output_shape[dnums.getOutputSpatialDimensions().data()[1]],
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 154.9K bytes - Viewed (0)