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Results 21 - 26 of 26 for 2x3x4xi32 (0.17 sec)
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tensorflow/compiler/mlir/lite/tests/lower-static-tensor-list.mlir
func.func @tensorlistConst(%arg0 : tensor<1xi32>) -> tensor<2x3xi32> { // CHECK-DAG: %[[ELEMENT0:.*]] = "tf.Const"() <{value = dense<[0, 1, 2]> : tensor<3xi32>}> : () -> tensor<3xi32> // CHECK-DAG: %[[ELEMENT1:.*]] = "tf.Const"() <{value = dense<[3, 4, 5]> : tensor<3xi32>}> : () -> tensor<3xi32> // CHECK: %[[LIST:.*]] = "tf.Pack"(%[[ELEMENT0]], %[[ELEMENT1]]) <{axis = 0 : i64}> : (tensor<3xi32>, tensor<3xi32>) -> tensor<2x3xi32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 39.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/convert_tf_xla_op_to_tf_op.cc
// Examples: // * If `xla_gather_op_output_type` == tensor<*xf32>, then it returns: // tensor<*xf32>. // * If `xla_gather_op_output_type` == tensor<3x5xi32> and `collapsed_dims` == // {0}, then it returns: tensor<1x3x5xi32>. // * If `xla_gather_op_output_type` == tensor<3x5xf32> and `collapsed_dims` == // {1, 3}, then it returns: tensor<3x1x5x1xf32>. Type GetSliceOpOutputType(Type xla_gather_op_output_type,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 13.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/optimize.mlir
func.func @ConvertIdentityGatherNdOp3D(%arg0: tensor<4x3x4xf32>) -> tensor<4x3x4xf32> { %cst = arith.constant dense<[[0], [1], [2], [3]]> : tensor<4x1xi32> %0 = "tfl.gather_nd"(%arg0, %cst) : (tensor<4x3x4xf32>, tensor<4x1xi32>) -> tensor<4x3x4xf32> func.return %0 : tensor<4x3x4xf32> // CHECK-LABEL: ConvertIdentityGatherNdOp3D // CHECK-SAME: (%[[ARG:.*]]: tensor<4x3x4xf32>) -> tensor<4x3x4xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 16 20:31:41 UTC 2024 - 284.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/compose-uniform-quantized-type.mlir
%0 = stablehlo.constant dense<3.000000e+00> : tensor<1x1xf32> // Input inverse scale. %1 = stablehlo.constant dense<1> : tensor<1x1xi8> // Input zero point. %2 = stablehlo.constant dense<5> : tensor<2x3xi32> // Quantized filter - the pattern expects i8 but i32 is given. %3 = stablehlo.constant dense<4> : tensor<1x3xi32> // Precalculated z1 * q2.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 14 17:10:32 UTC 2024 - 37K 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) -
tensorflow/compiler/mlir/lite/tests/prepare-composite-functions-tf.mlir
func.func private @dense_image_warp_invalid_input_shape(%arg0: tensor<2x4x4xf32>, %arg1: tensor<2x4x4x2xf32>) -> tensor<2x4x4x1xf32> attributes {tf._implements = "addons:DenseImageWarp"} // expected-warning @+1 {{Flow should be a 4D float tensor}} func.func private @dense_image_warp_invalid_flow_shape(%arg0: tensor<2x4x4x1xf32>, %arg1: tensor<2x4x4xf32>) -> tensor<2x4x4x1xf32> attributes {tf._implements = "addons:DenseImageWarp"}
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 122.1K bytes - Viewed (0)