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tensorflow/compiler/mlir/lite/ir/tfl_ops.td
element. For example, if you have a single image of shape `[height, width, channels]`, you can make it a batch of 1 image with `expand_dims(image, 0)`, which will make the shape `[1, height, width, channels]`. Other examples: ``` # 't' is a tensor of shape [2] shape(expand_dims(t, 0)) ==> [1, 2] shape(expand_dims(t, 1)) ==> [2, 1] shape(expand_dims(t, -1)) ==> [2, 1]
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/tests/canonicalize.mlir
%0 = "tf.EnsureShape"(%arg0) {shape = #tf_type.shape<10x20>} : (tensor<10x20xf32>) -> tensor<10x20xf32> %1 = "tf.EnsureShape"(%arg0) {shape = #tf_type.shape<?x20>} : (tensor<10x20xf32>) -> tensor<10x20xf32> // Failing case which should not be folded. // CHECK: %[[NF:.*]] = "tf.EnsureShape"(%arg0) <{shape = #tf_type.shape<20x10>}> %2 = "tf.EnsureShape"(%arg0) {shape = #tf_type.shape<20x10>} : (tensor<10x20xf32>) -> tensor<20x10xf32>
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/lite/stablehlo/transforms/uniform_quantized_stablehlo_to_tfl_pass.cc
new_filter_shape.push_back(filter_shape[transpose_dims[i]]); } auto get_array_idx = [](ArrayRef<int64_t> shape, const int i, const int j, const int k, const int l) -> int64_t { return (i * shape[1] * shape[2] * shape[3]) + (j * shape[2] * shape[3]) + (k * shape[3]) + l; }; // Transpose the filter value. // TODO: b/336203735 - Use `DenseElementsTransposer` instead of manual
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/lite/stablehlo/transforms/legalize_hlo.cc
// because starting from version 7, in presence of shape polymorphism JAX will // emit stablehlo.custom_call @shape_assertion to verify at compile time that // the code is used with compatible actual shapes. // TFLite runtime kernels support shape checking and shape inference to some // extent, it is okay to remove the shape assertion in most scenarios. However
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/jit/encapsulate_subgraphs_pass_test.cc
NodeBuilder node_builder(absl::StrCat(call_node, "_key_placeholder"), "Placeholder", opts.op_registry()); TensorShapeProto shape; shape.add_dim()->set_size(2); return opts.WithAttr("shape", shape) .WithAttr("dtype", DT_STRING) .WithAttr("_host_compute_call_node", call_node) .FinalizeBuilder(&node_builder); }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Feb 22 08:47:20 UTC 2024 - 113.3K bytes - Viewed (0) -
tensorflow/compiler/jit/extract_outside_compilation_pass.cc
.ok()) { return std::nullopt; } const PartialTensorShape shape = shapes[e->src_output()]; if (!shape.IsFullyDefined()) { return std::nullopt; } results[e->dst_input()] = shape; } return results; } string host_compute_node_name(const string& original_oc_name) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Mar 12 06:33:33 UTC 2024 - 104.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/tpu_rewrite.mlir
// CHECK-NOT: "tf.Shape"(%[[ARG_1]]) // CHECK-NOT: "tf.Shape"(%[[ARG_3]]) // CHECK: %[[ARG_0_SHAPE:[0-9]*]] = "tf.Shape"(%[[ARG_0]]) // CHECK: %[[ARG_2_SHAPE:[0-9]*]] = "tf.Shape"(%[[ARG_2]])
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 22:03:30 UTC 2024 - 172.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/flatbuffer_export.cc
GetTFLiteType(tensor_type.getElementType()).value(); std::vector<int32_t> shape; if (tensor_type.hasRank()) { llvm::ArrayRef<int64_t> shape_ref = tensor_type.getShape(); shape = std::vector<int32_t>(shape_ref.begin(), shape_ref.end()); } variant_params.push_back( tflite::CreateVariantSubType(builder_, builder_.CreateVector(shape), tflite_element_type, tensor_type.hasRank()));
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 12 21:41:49 UTC 2024 - 164.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/legalize-tf.mlir
// CHECK-LABEL:mul_with_high_dims_dynamic_shape_both_sides // CHECK: %[[SHAPE:.*]] = "tfl.shape"(%arg0) : (tensor<8x7x6x5x?x3x2x1xf32>) -> tensor<8xi64> // CHECK: %[[SHAPE_1:.*]] = "tfl.shape"(%arg1) : (tensor<?x3x2x1xf32>) -> tensor<4xi64> // CHECK: %[[BROADCAST_ARGS:.*]] = "tfl.broadcast_args"(%[[SHAPE]], %[[SHAPE_1]]) : (tensor<8xi64>, tensor<4xi64>) -> tensor<8xi64>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 05 01:54:33 UTC 2024 - 153.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/ops.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jun 06 19:09:08 UTC 2024 - 189.2K bytes - Viewed (0)