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tensorflow/compiler/mlir/tensorflow/tests/layout_optimization_to_nchw.mlir
// Check that Conv2D computed in NCHW format, and all redundant transpose // operations removed from the function. // CHECK: %[[CONV:[0-9]*]] = "tf.Conv2D"(%arg0, %arg1) // CHECK-SAME: data_format = "NCHW" // CHECK-SAME: -> tensor<1x8x32x32xf32> // CHECK: return %[[CONV]] func.return %4 : tensor<1x8x32x32xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Mar 24 05:47:26 UTC 2022 - 1.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/prepare-quantize-signed.mlir
%b = arith.constant dense<0.0> : tensor<3xf32> %conv = "tfl.conv_2d"(%arg0, %w, %b) {dilation_h_factor = 1 : i32, dilation_w_factor = 1 : i32, fused_activation_function = "RELU", padding = "SAME", stride_h = 1 : i32, stride_w = 1 : i32} : (tensor<1x5x5x3xf32>, tensor<3x3x3x3xf32>, tensor<3xf32>) -> tensor<1x5x5x3xf32> func.return %conv : tensor<1x5x5x3xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 18.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/optimize-after-quantization.mlir
// CHECK: %[[weight:.*]] = arith.constant dense<3.000000e+00> : tensor<3x3x3x3xf32> // CHECK: %[[bias:.*]] = arith.constant dense<[1.500000e+00, 3.000000e+00, 4.500000e+00]> // CHECK: %[[conv:.*]] = "tfl.conv_2d"(%arg0, %[[weight]], %[[bias]]) // CHECK: return %[[conv]] : tensor<256x8x7x3xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Jan 05 18:35:42 UTC 2024 - 1.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/modify_io_nodes.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 19.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/fuse_mhlo_convolution.mlir
// CHECK: %[[CONV:.+]] = mhlo.convolution(%[[INPUT]], %[[NEW_FILTER]]) dim_numbers = [b, 0, 1, f]x[0, 1, i, o]->[b, 0, 1, f], window = {stride = [1, 1], pad = {{\[\[}}0, 0], [0, 0]], rhs_dilate = [1, 1]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} : (tensor<?x256x256x3xf32>, tensor<1x1x3x2xf32>) -> tensor<?x256x256x2xf32> // CHECK: %[[SHAPE:.+]] = shape.shape_of %[[CONV]] : tensor<?x256x256x2xf32> -> tensor<4xindex>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Apr 06 15:32:52 UTC 2024 - 4.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/optimize.td
Pat<(TF_MulOp:$mul (TF_Conv2DOp:$conv $input, (Arith_ConstantOp:$filter F32ElementsAttr:$filter_value), $strides, $use_cudnn, $padding, $explicit_padding, IsDataFormatNHWC:$data_format, $dilations), (Arith_ConstantOp:$multiplier F32ElementsAttr:$mul_value)), // TODO(karimnosseir): Add check for $conv is of rank 4. (TF_Conv2DOp $input,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Apr 22 07:31:23 UTC 2023 - 5.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/quantize_composite_functions_weight_only.mlir
// CHECK: %[[CONV:.+]] = stablehlo.convolution(%[[ARG1]], %[[ARG2]]) // CHECK-SAME: (tensor<1x3x4x3xf32>, tensor<2x3x3x2x!quant.uniform<i8<-127:127>:f32, 0.0023622048182750312>>) -> tensor<1x3x4x2xf32> // CHECK: return %[[CONV]] // ----- // Test that per-channel weight-only quantized dot_general op is produced when
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 09 05:56:10 UTC 2024 - 9.4K bytes - Viewed (0) -
subprojects/core/src/test/groovy/org/gradle/api/internal/project/DefaultProjectTest.groovy
String expectedValue = 'somevalue' when: project.convention.plugins.test = new TestConvention() project.conv = expectedValue then: project.conv == expectedValue project.convention.plugins.test.conv == expectedValue child1.conv == expectedValue } def setPropertyAndPropertyMissingWithProjectAndConventionProperty() { given:
Registered: Wed Jun 12 18:38:38 UTC 2024 - Last Modified: Fri Mar 08 13:46:07 UTC 2024 - 35.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/add_dump_tensor_op.mlir
%1 = "tf.PartitionedCall"(%arg0, %cst, %cst_0) {_tfl_quant_trait = "fully_quantizable", config = "", config_proto = "", executor_type = "", f = @composite_conv2d_with_bias_and_relu6_fn_1} : (tensor<1x2x2x3xf32>, tensor<2x2x3x2xf32>, tensor<2xf32>) -> tensor<*xf32> loc(callsite("test@conv"("Conv2D_1") at "QuantizationUnit(\12\08Conv2D_1\1a\04conv)"))
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Mar 22 22:55:22 UTC 2024 - 37.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/prepare-tf-fake-quant-4bit.mlir
// CHECK: %[[DEQUANTIZE:.*]] = "tfl.dequantize"(%[[QUANTIZE]]) // CHECK: %[[CONV:.*]] = "tfl.conv_2d"(%arg0, %[[DEQUANTIZE]], %[[CONSTANT]]) // CHECK: return %[[CONV]] } // CHECK-LABEL: perChannelFakeQuantWithConv2D func.func @perChannelFakeQuantWithConv2D(tensor<256x32x32x3xf32>) -> (tensor<256x8x7x16xf32>) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 22K bytes - Viewed (0)