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tensorflow/compiler/mlir/quantization/tensorflow/tests/insert_quantized_functions.mlir
// CHECK-SAME: tf_quant.quantized_ops = ["DepthwiseConv2D", "BiasAdd", "Relu"] // CHECK: func private @quantized_matmul_with_bias_fn // CHECK: func private @quantized_matmul_with_bias_and_relu_fn // CHECK: func private @quantized_matmul_with_bias_and_relu6_fn // CHECK: func private @quantized_matmul_fn // CHECK-SAME: tf_quant.quantized_ops = ["MatMul"]
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Aug 29 01:13:58 UTC 2023 - 3.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/insert_quantized_functions_drq.mlir
// CHECK-NOT: func private @internal_matmul_fn // CHECK: func private @quantized_matmul_fn // CHECK-SAME: tf_quant.quantized_ops = ["MatMul"] // CHECK: func private @quantized_conv2d_fn // CHECK-SAME: tf_quant.quantized_ops = ["Conv2D"] // CHECK: func private @quantized_depthwise_conv2d_fn // CHECK-SAME: tf_quant.quantized_ops = ["DepthwiseConv2D"] // UQ-CHECK: func private @quantized_conv2d_fn
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Dec 01 12:06:54 UTC 2022 - 1K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/quantize_composite_functions_weight_only.mlir
func.return %1: tensor<*xf32> } func.func private @composite_matmul_fn_1(%arg0: tensor<2x12xf32>, %arg1: tensor<12x2xf32>) -> tensor<*xf32> attributes {tf_quant.composite_function} { %0 = "tf.MatMul"(%arg0, %arg1) {attr_map = "0:transpose_a,1:transpose_b", device = "", transpose_a = false, transpose_b = false} : (tensor<2x12xf32>, tensor<12x2xf32>) -> tensor<*xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 11.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/quantize_composite_functions.mlir
// CHECK-DAG: %[[out_scale:.*]] = "tf.Const"() <{value = dense<5.000000e-02> : tensor<f32>}> // CHECK-DAG: %[[out_zp:.*]] = "tf.Const"() <{value = dense<-1> : tensor<i32>}> // CHECK-DAG: %[[b_quant:.*]] = "tf.Const"() <{value = dense<[-62500, 75000]> : tensor<2xi32>}> // CHECK-DAG: %[[w_quant:.*]] = "tf.Const"() <{value = dense<{{\[\[\[\[}}40, 20] // CHECK-DAG: {{\[\[\[}}-87, -42] // CHECK: %[[quantize:.*]] = "tf.PartitionedCall"(%arg0, %[[in_scale]], %[[in_zp]])
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Nov 06 01:23:21 UTC 2023 - 15.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/quantized_function_library_uniform_quantized_drq.mlir
%input : tensor<*xf32>, %weight : tensor<*x!tf_type.qint8>, %weight_scale : tensor<*xf32>, %weight_zp : tensor<*xi32>) -> tensor<*xf32> attributes {tf_quant.quantized_ops = ["Conv2D"]} { %out = "tf.UniformQuantizedConvolutionHybrid"(%input, %weight, %weight_scale, %weight_zp) { Tlhs = "tfdtype$DT_FLOAT", Trhs = "tfdtype$DT_QINT8",
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Dec 01 12:06:54 UTC 2022 - 3.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/quantize_composite_functions_drq.mlir
func.return %1: tensor<*xf32> } func.func private @composite_matmul_fn_1(%arg0: tensor<2x12xf32>, %arg1: tensor<12x2xf32>) -> tensor<*xf32> attributes {tf_quant.composite_function} { %0 = "tf.MatMul"(%arg0, %arg1) {attr_map = "0:transpose_a,1:transpose_b", device = "", transpose_a = false, transpose_b = false} : (tensor<2x12xf32>, tensor<12x2xf32>) -> tensor<*xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Jan 05 18:35:42 UTC 2024 - 9.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/insert_calibration_statistics_saver.mlir
// ----- // No CustomAggregator ops exist. func.func private @composite_conv2d_with_bias_and_relu6_fn_1(%arg0: tensor<1x3x4x3xf32>, %arg1: tensor<2x3x3x2xf32>, %arg2: tensor<2xf32>) -> tensor<1x2x2x2xf32> attributes {tf_quant.composite_function} {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 01:09:50 UTC 2024 - 24.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/quantize_composite_functions_xla.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Jan 08 01:16:10 UTC 2024 - 25.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/prepare_quantize_drq_per_channel.mlir
func.return %1: tensor<*xf32> } func.func private @composite_matmul_fn(%arg0: tensor<1x2x2x3xf32>, %arg1: tensor<2x1024xf32>) -> tensor<*xf32> attributes {tf_quant.composite_function} { %0 = "tf.MatMul"(%arg0, %arg1) {attr_map = "0:transpose_a,1:transpose_a", device = "", transpose_a = false, transpose_b = false} : (tensor<1x2x2x3xf32>, tensor<2x1024xf32>) -> tensor<*xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 6.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/lift_quantizable_spots_as_functions_with_quantization_specs.mlir
// DISABLE-ALL-DOT-GENERAL: return %[[XLA_CALL_MODULE:.+]] : tensor<1x1x64xf32> // DISABLE-ALL-DOT-GENERAL: } // DISABLE-ALL-DOT-GENERAL-LABEL: private @composite_dot_general_fn_1 // DISABLE-ALL-DOT-GENERAL-SAME: tf_quant.composite_function // DISABLE-ALL-DOT-GENERAL: %[[DOT_GENERAL:.+]] = stablehlo.dot_general %arg0, %arg1 // DISABLE-ALL-DOT-GENERAL: return %[[DOT_GENERAL:.+]] : tensor<1x1x64xf32> // DISABLE-ALL-DOT-GENERAL: } // -----
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Apr 02 18:09:38 UTC 2024 - 8.1K bytes - Viewed (0)