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Results 21 - 30 of 93 for conv_3d (0.19 sec)
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tensorflow/compiler/mlir/quantization/tensorflow/ops/tf_op_quant_spec.cc
if (function_name.contains("with_bias")) { spec->biases_params[2] = {{0, 1}, quant::GetUniformQuantizedTypeForBias}; } } else if (function_name.contains("conv3d")) { spec->coeff_op_quant_dim[1] = 4; if (function_name.contains("with_bias")) { spec->biases_params[2] = {{0, 1}, quant::GetUniformQuantizedTypeForBias}; }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 6.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/prepare-tf-fake-quant-4bit.mlir
// CHECK: %[[QUANTIZE:.*]] = "tfl.quantize"(%[[CONSTANT0]]) <{qtype = tensor<16x3x3x3x!quant.uniform<u4:f32, 1.000000e+00>>}> // 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) -
tensorflow/compiler/mlir/lite/tests/flatbuffer2mlir/import_json.json
// RUN: json_to_flatbuffer %p/test_schema.fbs %s | flatbuffer_translate --tflite-flatbuffer-to-mlir -o - | FileCheck %s // CHECK: %[[CST:.*]] = "tfl.no_value"() <{value}> : () -> none // CHECK: %[[RES0:.*]] = "tfl.conv_2d"(%arg0, %arg1, %[[CST]]) <{dilation_h_factor = 1 : i32, dilation_w_factor = 1 : i32, fused_activation_function = "NONE", padding = "SAME", stride_h = 1 : i32, stride_w = 1 : i32}> : (tensor<256x32x32x3xf32>, tensor<16x3x3x3xf32>, none) -> tensor<256x32x32x16xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 1.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/prepare-quantize-signed.mlir
// CHECK: %[[conv:.*]] = "tfl.conv_2d"(%arg0, %[[dq]] // PerTensor: %[[cst:.*]] = arith.constant dense<1.270000e+02> : tensor<3x3x3x3xf32> // PerTensor: %[[q:.*]] = "tfl.quantize"(%[[cst]]) <{qtype = tensor<3x3x3x3x!quant.uniform<i8<-127:127>:f32, 1.000000e+00>>}> {volatile} // PerTensor: %[[dq:.*]] = "tfl.dequantize"(%[[q]]) // PerTensor: %[[conv:.*]] = "tfl.conv_2d"(%arg0, %[[dq]] } // CHECK-LABEL: prepareConv2D
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/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/tests/optimize_no_verify.mlir
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/transforms/fuse_convolution_pass.cc
mul_op.getLoc(), conv_op.getType(), conv_op.getLhs(), new_filter, conv_op.getWindowStridesAttr(), conv_op.getPaddingAttr(), conv_op.getLhsDilationAttr(), conv_op.getRhsDilationAttr(), conv_op.getWindowReversalAttr(), conv_op.getDimensionNumbers(), conv_op.getFeatureGroupCount(), conv_op.getBatchGroupCount(), conv_op.getPrecisionConfigAttr());
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Feb 22 22:21:19 UTC 2024 - 8.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/quantized_function_library.mlir
equation = "", attr_map = "equation:0" } : (tensor<*xi32>, tensor<*xi32>) -> tensor<*xi32> func.return %4 : tensor<*xi32> } for main_op in ["Conv2D", "DepthwiseConv2D", "MatMul", "Conv3D", "BatchMatMul", "Einsum"] { parameters[ {"quantized_ops": ["${main_op}", "BiasAdd"], "act_func": "internal_requantize_no_activation_fn", "output_type": "i8"},
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Jan 08 01:16:10 UTC 2024 - 30.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/ir/tfl_ops.td
TFL_ResourceTensor:$resource_id ); let results = (outs TFL_TensorOf<[F32, F64, I1, UI8, I8, QI8, QUI8, I32, I64, QI16, Complex<F<32>>, Complex<F<64>>]>:$result); } def TFL_Conv3DOp : TFL_Op<"conv_3d", [ Pure, AccumulatorUniformScale<2, 0, 1>, TFL_OperandHasRank<0, 5>, TFL_OperandHasRank<1, 5>, // Channel dimension in input and filter should match.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jun 06 19:09:08 UTC 2024 - 186K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/default_quant_params.mlir
%1 = "tfl.dequantize"(%arg1) : (tensor<32x3x3x3x!quant.uniform<u8<1:255>:f32, 1.0>>) -> tensor<32x3x3x3xf32> %2 = "tfl.dequantize"(%arg2) : (tensor<32x!quant.uniform<i32:f32, 1.0>>) -> tensor<32xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 8.8K bytes - Viewed (0)