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Results 81 - 90 of 229 for transposes (0.26 sec)
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tensorflow/compiler/mlir/lite/stablehlo/tests/composite-lowering.mlir
// CHECK-SAME: %[[VAL_0:.*]]: tensor<1x3x6x6xf32>) -> tensor<*xf32> { // CHECK: %[[VAL_1:.*]] = arith.constant dense<[0, 2, 3, 1]> : tensor<4xi32> // CHECK: %[[VAL_2:.*]] = "tfl.transpose"(%[[VAL_0]], %[[VAL_1]]) : (tensor<1x3x6x6xf32>, tensor<4xi32>) -> tensor<1x6x6x3xf32> // CHECK: %[[VAL_3:.*]] = arith.constant dense<0> : tensor<4x2xi32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jun 06 18:45:51 UTC 2024 - 32.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfr/README.md
derived_attrs=['T: {float, int8}'], outputs=['o: T']) def _composite_fully_connected(input_, filter_, bias, act): res = tf.raw_ops.MatMul( a=input_, b=filter_, transpose_a=False, transpose_b=True) res = tf.raw_ops.Add(x=res, y=bias) if act == 'RELU': return tf.raw_ops.Relu(features=res) elif act == 'RELU6': return tf.raw_ops.Relu6(features=res) elif act == 'TANH':
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Mar 29 18:32:13 UTC 2022 - 6.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/utils/utils.td
// Constraint that checks if the transpose op is trivial. Trivial means that // the permutation is a cyclic permutation of the original shape with only the // identity dimensions permuted. def IsTransposeTrivial : Constraint<CPred< "TFL::IsTransposeTrivial($0.getType().cast<ShapedType>().getShape(), $1)">>; // Constraint that checks if the reshape op is equivalent to a transpose op.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Apr 30 00:40:15 UTC 2024 - 4.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/legalize-tf.mlir
%0 = "tf.Transpose"(%arg0, %cst): (tensor<2x3xf32>, tensor<2xi64>) -> tensor<3x2xf32> func.return %0 : tensor<3x2xf32> // CHECK-LABEL: tranpose_int64_perm // CHECK: "tfl.transpose" } func.func @tranpose_arg32(%arg0: tensor<2x3xf32>, %arg1: tensor<2xi32>) -> tensor<3x2xf32> { %0 = "tf.Transpose"(%arg0, %arg1): (tensor<2x3xf32>, tensor<2xi32>) -> tensor<3x2xf32>
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/stablehlo/tests/uniform-quantized-stablehlo-to-tfl.mlir
// CHECK: return %[[TRANSPOSE]] // ----- // Tests that a float `stablehlo.transpose` is not converted to `tfl.transpose`. func.func @transpose_float(%arg0: tensor<2x3x4xf32>) -> tensor<4x3x2xf32> { %0 = stablehlo.transpose %arg0, dims = [2, 1, 0] : (tensor<2x3x4xf32>) -> tensor<4x3x2xf32> return %0 : tensor<4x3x2xf32> } // CHECK-LABEL: transpose_float // CHECK-NOT: tfl.transpose // CHECK: stablehlo.transpose
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 14 17:10:32 UTC 2024 - 106.2K bytes - Viewed (0) -
android/guava/src/com/google/common/collect/Tables.java
} } /** * Creates a transposed view of a given table that flips its row and column keys. In other words, * calling {@code get(columnKey, rowKey)} on the generated table always returns the same value as * calling {@code get(rowKey, columnKey)} on the original table. Updating the original table * changes the contents of the transposed table and vice versa. *
Registered: Wed Jun 12 16:38:11 UTC 2024 - Last Modified: Sun Jun 02 13:36:19 UTC 2024 - 26.3K bytes - Viewed (0) -
src/internal/dag/alg.go
// Copyright 2022 The Go Authors. All rights reserved. // Use of this source code is governed by a BSD-style // license that can be found in the LICENSE file. package dag // Transpose reverses all edges in g. func (g *Graph) Transpose() { old := g.edges g.edges = make(map[string]map[string]bool) for _, n := range g.Nodes { g.edges[n] = make(map[string]bool) } for from, tos := range old { for to := range tos {
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Thu Aug 04 15:31:44 UTC 2022 - 1.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/components/pre_calibration_component.mlir
// CHECK: @main(%[[ARG:.+]]: tensor<1x8x4x4xf32>) -> tensor<1x8x4x4xf32> // Contains the `stablehlo.transpose` op of the arg (e.g. [b, f, 0, 1] to // [b, 0, 1, f]). The weight constant is folded into [0, 1, i, o] format. // CHECK-DAG: %[[CST:.+]] = stablehlo.constant dense<3.000000e+00> : tensor<3x3x8x8xf32> // CHECK: %[[TRANSPOSE_1:.+]] = stablehlo.transpose %arg0, dims = [0, 2, 3, 1] : (tensor<1x8x4x4xf32>) -> tensor<1x4x4x8xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 10 04:07:09 UTC 2024 - 5.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/tf_saved_model/duplicate_method_names_v1.py
# CHECK-SAME: {{.*}}) # CHECK-SAME: attributes {{.*}} tf_saved_model.exported_names = ["key2"] def Test(): x = tf.constant(1.0, shape=(3, 3)) y = tf.constant(1.0, shape=(3, 3)) s = tf.transpose(x) t = tf.transpose(y) tensor_info_s = tf.compat.v1.saved_model.utils.build_tensor_info(s) tensor_info_t = tf.compat.v1.saved_model.utils.build_tensor_info(t)
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Sep 28 21:37:05 UTC 2021 - 2K bytes - Viewed (0) -
guava/src/com/google/common/collect/Tables.java
} } /** * Creates a transposed view of a given table that flips its row and column keys. In other words, * calling {@code get(columnKey, rowKey)} on the generated table always returns the same value as * calling {@code get(rowKey, columnKey)} on the original table. Updating the original table * changes the contents of the transposed table and vice versa. *
Registered: Wed Jun 12 16:38:11 UTC 2024 - Last Modified: Mon Mar 04 22:45:41 UTC 2024 - 26.3K bytes - Viewed (0)