| # RUN: tf_tfl_translate -tf-input-arrays=input0,input1 -tf-input-shapes=4:4 -tf-input-data-types=DT_FLOAT,DT_FLOAT -tf-output-arrays=Add -tf-inference-type=DT_QUINT8 -tf-input-min-values='-2,-3' -tf-input-max-values='2,3' --quant-stats=%s.stats %s -o - --output-mlir 2>&1 \ |
| # RUN: | FileCheck --check-prefix=MLIR %s |
| # RUN: tf_tfl_translate -tf-input-arrays=input0,input1 -tf-input-shapes=4:4 -tf-input-data-types=DT_FLOAT,DT_FLOAT -tf-output-arrays=Add -tf-inference-type=DT_QUINT8 -tf-input-min-values='-2,-3' -tf-input-max-values='2,3' --quant-stats=%s.stats %s -o - | flatbuffer_to_string - \ |
| # RUN: | FileCheck %s |
| |
| node { |
| name: "Add" |
| op: "Add" |
| input: "input0" |
| input: "input1" |
| attr { |
| key: "T" |
| value { |
| type: DT_FLOAT |
| } |
| } |
| } |
| node { |
| name: "input0" |
| op: "Placeholder" |
| attr { |
| key: "dtype" |
| value { |
| type: DT_FLOAT |
| } |
| } |
| } |
| node { |
| name: "input1" |
| op: "Placeholder" |
| attr { |
| key: "dtype" |
| value { |
| type: DT_FLOAT |
| } |
| } |
| } |
| versions { |
| producer: 27 |
| } |
| |
| # MLIR-LABEL: func @main(%arg0: tensor<4x!quant.uniform<u8:f32, 0.015686274509803921:128>>, %arg1: tensor<4x!quant.uniform<u8:f32, 0.023529411764705882:128>>) -> tensor<4x!quant.uniform<u8:f32, 0.0078431372549019607:128>> |
| # MLIR-SAME: attributes {tf.entry_function = {control_outputs = "", inputs = "input0,input1", outputs = "Add"}} { |
| # MLIR-NEXT: %[[add:.*]] = "tfl.add"(%arg0, %arg1) {fused_activation_function = "NONE"} : (tensor<4x!quant.uniform<u8:f32, 0.015686274509803921:128>>, tensor<4x!quant.uniform<u8:f32, 0.023529411764705882:128>>) -> tensor<4x!quant.uniform<u8:f32, 0.0078431372549019607:128>> |
| # MLIR-NEXT: return %[[add]] : tensor<4x!quant.uniform<u8:f32, 0.0078431372549019607:128>> |
| # MLIR-NEXT: } |
| |
| # CHECK-LABEL: { |
| # CHECK-NEXT: version: 3, |
| # CHECK-NEXT: operator_codes: [ { |
| # CHECK-NEXT: version: 1 |
| # CHECK-NEXT: } ], |
| # CHECK-NEXT: subgraphs: [ { |
| # CHECK-NEXT: tensors: [ { |
| # CHECK-NEXT: shape: [ 4 ], |
| # CHECK-NEXT: type: UINT8, |
| # CHECK-NEXT: buffer: 1, |
| # CHECK-NEXT: name: "input0", |
| # CHECK-NEXT: quantization: { |
| # CHECK-NEXT: scale: [ 0.015686 ], |
| # CHECK-NEXT: zero_point: [ 128 ] |
| # CHECK-NEXT: } |
| # CHECK-NEXT: }, { |
| # CHECK-NEXT: shape: [ 4 ], |
| # CHECK-NEXT: type: UINT8, |
| # CHECK-NEXT: buffer: 2, |
| # CHECK-NEXT: name: "input1", |
| # CHECK-NEXT: quantization: { |
| # CHECK-NEXT: scale: [ 0.023529 ], |
| # CHECK-NEXT: zero_point: [ 128 ] |
| # CHECK-NEXT: } |
| # CHECK-NEXT: }, { |
| # CHECK-NEXT: shape: [ 4 ], |
| # CHECK-NEXT: type: UINT8, |
| # CHECK-NEXT: buffer: 3, |
| # CHECK-NEXT: name: "Add", |
| # CHECK-NEXT: quantization: { |
| # CHECK-NEXT: scale: [ 0.007843 ], |
| # CHECK-NEXT: zero_point: [ 128 ] |
| # CHECK-NEXT: } |
| # CHECK-NEXT: } ], |
| # CHECK-NEXT: inputs: [ 0, 1 ], |
| # CHECK-NEXT: outputs: [ 2 ], |
| # CHECK-NEXT: operators: [ { |
| # CHECK-NEXT: inputs: [ 0, 1 ], |
| # CHECK-NEXT: outputs: [ 2 ], |
| # CHECK-NEXT: builtin_options_type: AddOptions, |
| # CHECK-NEXT: builtin_options: { |
| # CHECK-EMPTY: |
| # CHECK-NEXT: } |
| # CHECK-NEXT: } ], |
| # CHECK-NEXT: name: "main" |
| # CHECK-NEXT: } ], |
| # CHECK-NEXT: description: "MLIR Converted.", |
| # CHECK-NEXT: buffers: [ { |
| # CHECK-EMPTY: |
| # CHECK-NEXT: }, { |
| # CHECK-EMPTY: |
| # CHECK-NEXT: }, { |
| # CHECK-EMPTY: |
| # CHECK-NEXT: }, { |
| # CHECK: data: [ 49, 46, 53, 46, 48, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ] |
| # CHECK-NEXT: } ] |
| |