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Results 41 - 50 of 55 for _output_shapes (0.22 sec)
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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/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) -
tensorflow/compiler/mlir/lite/transforms/optimize.cc
mlir::cast<ShapedType>(input.getType()).getShape(); ArrayRef<int64_t> output_shape = mlir::cast<ShapedType>(output.getType()).getShape(); int64_t agg_value = 1; for (size_t i = agg_start_idx; i < input_shape.size() - 1; ++i) { agg_value *= input_shape[i]; } return (agg_value == output_shape[agg_start_idx]); } // Returns whether the given type `a` is broadcast-compatible with `b`.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Apr 30 00:40:15 UTC 2024 - 102.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/flatbuffer_import.cc
for (auto s : new_shape) { shape.push_back( builder.getI32IntegerAttr(mlir::TFL::ConvertToTfliteSize(s))); } auto output_shape = DenseElementsAttr::get(shape_type, shape); auto shape_op = builder.create<tfl::ConstOp>(loc, output_shape); op_state.addOperands({shape_op}); } op_state.addTypes({type}); }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 21 18:21:50 UTC 2024 - 66.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/legalize_patterns.td
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 04 13:30:42 UTC 2024 - 28.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/canonicalize.mlir
%4 = "tf.Case"(%2, %arg0, %arg1) {branches = [@sub, @add], output_shapes = [#tf_type.shape<>], device = "noodle", is_stateless = false} : (tensor<i32>, tensor<f32>, tensor<f32>) -> tensor<f32> // CHECK: PartitionedCall // CHECK-SAME: f = @sub // CHECK-SAME: _cluster_launch = "not_ready" // CHECK-SAME: device = "noodle"
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 09 22:07:10 UTC 2024 - 132.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/ir/tf_generated_ops.td
let summary = "A container for an iterator resource."; let arguments = (ins ConfinedAttr<TypeArrayAttr, [ArrayMinCount<1>]>:$output_types, ConfinedAttr<TF_ShapeAttrArray, [ArrayMinCount<1>]>:$output_shapes ); let results = (outs Res<TF_ResourceTensor, [{A handle to the iterator that can be passed to a "MakeIterator" or "IteratorGetNext" op. In contrast to Iterator, AnonymousIterator prevents
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 11 23:24:08 UTC 2024 - 793K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/legalize_tf.cc
Value none = rewriter.create<TFL::NoValueOp>( op->getLoc(), rewriter.getNoneType(), rewriter.getUnitAttr()); Value output_shape = CreateCastToInt32(tf_op.getInputSizes(), op->getLoc(), rewriter); rewriter.replaceOpWithNewOp<TFL::Conv3DTransposeOp>( op, tf_op.getType(), output_shape, tf_op.getFilter(), tf_op.getOutBackprop(), /*bias=*/none, dilation_depth_factor, dilation_height_factor,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon May 20 20:06:54 UTC 2024 - 45.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/transforms/uniform_quantized_stablehlo_to_tfl_pass.cc
.getScale(), /*filter_scales=*/filter_quantized_type.getScales()); const ArrayRef<int64_t> output_shape = op->getResult(0).getType().cast<TensorType>().getShape(); const SmallVector<int64_t, 1> bias_shape = { output_shape[output_shape.size() - 1]}; // `tfl.fully_connected`'s `GetChannelDimIndex` is 0. const auto bias_quantized_type =
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Apr 22 09:00:19 UTC 2024 - 99.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/transforms/legalize_tf.cc
// Shape of the final output. (Except for dimension folding in the // single diagonal case.) Shape output_shape; for (int i = 0; i < num_dims - 2; i++) { output_shape.push_back(input_type.getDimSize(i)); } output_shape.push_back(num_diags); output_shape.push_back(max_diag_len); // A slice is the shape of what GatherOp copies per lookup. So the last
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 11 20:00:43 UTC 2024 - 291.8K bytes - Viewed (0)