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tensorflow/compiler/mlir/lite/tests/prepare-tf.mlir
%4 = "tf.MatMul"(%arg0, %3) {device = "", transpose_a = false, transpose_b = false} : (tensor<2x3xf32>, tensor<3x4xf32>) -> tensor<2x4xf32> %5 = "tf.Identity"(%4) {device = ""} : (tensor<2x4xf32>) -> tensor<2x4xf32> %6 = "tf.Identity"(%5) {device = ""} : (tensor<2x4xf32>) -> tensor<2x4xf32> func.return %6 : tensor<2x4xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 29 07:26:59 UTC 2024 - 59.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/tests/legalize-tf.mlir
%0:2 = "tf.Split"(%cst, %input) : (tensor<i32>, tensor<4x?x4xf32>) -> (tensor<2x?x4xf32>, tensor<2x?x4xf32>) func.return %0#0, %0#1 : tensor<2x?x4xf32>, tensor<2x?x4xf32> } // ----- // CHECK-LABEL: @split_match_and_split_into_two func.func @split_match_and_split_into_two(%input: tensor<4x6xf32>) -> (tensor<2x6xf32>, tensor<2x6xf32>) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon May 06 18:46:23 UTC 2024 - 335.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/prepare-quantize.mlir
%4 = "tfl.concatenation"(%1, %3) {axis = -1 : i32, fused_activation_function = "NONE"} : (tensor<2x1xf32>, tensor<2x3xf32>) -> tensor<2x4xf32> %5 = "tfl.add"(%4, %arg2) {fused_activation_function = "NONE"} : (tensor<2x4xf32>, tensor<2x4xf32>) -> tensor<2x4xf32> func.return %5: tensor<2x4xf32> // MixedPrecision-NEXT: %[[q:.*]] = "tfl.quantize"(%arg0) // MixedPrecision-NEXT: %[[dq:.*]] = "tfl.dequantize"(%[[q]])
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 67.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/tf-ops.mlir
func.func @testPackedTPUPartitionedInputV2(tensor<2x4xf32>, tensor<2x4xf32>) -> tensor<4x4xf32> { ^bb0(%arg0: tensor<2x4xf32>, %arg1: tensor<2x4xf32>): // expected-error @+1 {{expected 1 inputs, got 2}} %0 = "tf.TPUPartitionedInputV2"(%arg0, %arg1) {partition_dims = [2, 1], is_packed = true} : (tensor<2x4xf32>, tensor<2x4xf32>) -> tensor<4x4xf32> func.return %0 : tensor<4x4xf32> } // -----
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 23 14:40:35 UTC 2023 - 236.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/layout_optimization_move_transposes_end.mlir
exponential_avg_factor = 1.0 : f32, is_training = false } : (tensor<1x112x112x64xf32>, tensor<64xf32>, tensor<64xf32>, tensor<64xf32>, tensor<64xf32>) -> (tensor<1x112x112x64xf32>, tensor<64xf32>, tensor<64xf32>, tensor<64xf32>, tensor<64xf32>, tensor<64xf32>) func.return %2#0 : tensor<1x112x112x64xf32> } // CHECK-LABEL: func @fold_into_pad_with_extra_uses
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 9.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/quantization/tensorflow/tests/fallback_to_flex_ops_legacy.mlir
} // CHECK-LABEL: softmax func.func @softmax(%arg0: tensor<8x16xf32>) -> tensor<8x16xf32> { %0 = "tf.Softmax"(%arg0) : (tensor<8x16xf32>) -> tensor<8x16xf32> func.return %0 : tensor<8x16xf32> // CHECK: %[[SOFTMAX_0:.*]] = "tf.Softmax"(%arg0) : (tensor<8x16xf32>) -> tensor<8x16xf32> // CHECK: return %[[SOFTMAX_0]] : tensor<8x16xf32> } // CHECK-LABEL: conv2d_backprop_input_with_add
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 5.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/compose-uniform-quantized-type.mlir
%19 = stablehlo.convert %18 : (tensor<8x16x4xi32>) -> tensor<8x16x4xf32> %20 = stablehlo.broadcast_in_dim %9, dims = [0, 1, 2] : (tensor<1x1x1xf32>) -> tensor<8x16x4xf32> %21 = stablehlo.multiply %19, %20 : tensor<8x16x4xf32> // * s1 s2 %22 = call @uniform_quantize_1(%21, %7, %8) : (tensor<8x16x4xf32>, tensor<1x1x1xf32>, tensor<1x1x1xi8>) -> tensor<8x16x4xi8>
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/tests/prepare-tf-fake-quant.mlir
func.func @fakeQuantPerChannelForActivation(%arg0: tensor<8x4xf32>) -> (tensor<8x4xf32>) { %arg1 = arith.constant dense<[0.0, -1.0, 1.0, 0.0]> : tensor<4xf32> %arg2 = arith.constant dense<[255.0, 254.0, 256.0, 1.0e-9]> : tensor<4xf32> %0 = "tf.FakeQuantWithMinMaxVarsPerChannel"(%arg0, %arg1, %arg2) {num_bits = 5, narrow_range = false} : (tensor<8x4xf32>, tensor<4xf32>, tensor<4xf32>) -> tensor<8x4xf32> func.return %0 : tensor<8x4xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 20.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/optimize.mlir
%cst = arith.constant dense<[3, 4]> : tensor<2xi32> %cst_0 = arith.constant dense<1.000000e+00> : tensor<3x4xf32> %0 = "tfl.reshape"(%arg0, %cst) : (tensor<*xf32>, tensor<2xi32>) -> tensor<3x4xf32> %1 = "tfl.add"(%0, %cst_0) {fused_activation_function = "NONE"} : (tensor<3x4xf32>, tensor<3x4xf32>) -> tensor<3x4xf32> func.return %1 : tensor<3x4xf32> // CHECK-LABEL: ReshapeAddUnknownShape
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/tests/flatbuffer2mlir/lstm.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 20.4K bytes - Viewed (0)