| /frameworks/ml/nn/runtime/test/specs/V1_1/ |
| mean.mod.py | 4 keepDims = Int32Scalar("keepDims", 0)
7 model = model.Operation("MEAN", i1, axis, keepDims).To(output)
|
| mean_float_1.mod.py | 4 keepDims = Int32Scalar("keepDims", 0)
7 model = model.Operation("MEAN", i1, axis, keepDims).To(output)
|
| mean_float_1_relaxed.mod.py | 20 keepDims = Int32Scalar("keepDims", 0)
23 model = model.Operation("MEAN", i1, axis, keepDims).To(output)
|
| mean_float_2.mod.py | 4 keepDims = Int32Scalar("keepDims", 1)
7 model = model.Operation("MEAN", i1, axis, keepDims).To(output)
|
| mean_float_2_relaxed.mod.py | 20 keepDims = Int32Scalar("keepDims", 1)
23 model = model.Operation("MEAN", i1, axis, keepDims).To(output)
|
| mean_quant8_1.mod.py | 4 keepDims = Int32Scalar("keepDims", 0)
7 model = model.Operation("MEAN", i1, axis, keepDims).To(output)
|
| mean_quant8_2.mod.py | 4 keepDims = Int32Scalar("keepDims", 1)
7 model = model.Operation("MEAN", i1, axis, keepDims).To(output)
|
| mean_relaxed.mod.py | 20 keepDims = Int32Scalar("keepDims", 0)
23 model = model.Operation("MEAN", i1, axis, keepDims).To(output)
|
| /frameworks/ml/nn/runtime/test/generated/models/ |
| mean.model.cpp | 10 auto keepDims = model->addOperand(&type2);
16 model->setOperandValue(keepDims, keepDims_init, sizeof(int32_t) * 1);
17 model->addOperation(ANEURALNETWORKS_MEAN, {input, axis, keepDims}, {output});
|
| mean_float_1.model.cpp | 10 auto keepDims = model->addOperand(&type2);
16 model->setOperandValue(keepDims, keepDims_init, sizeof(int32_t) * 1);
17 model->addOperation(ANEURALNETWORKS_MEAN, {input, axis, keepDims}, {output});
|
| mean_float_1_relaxed.model.cpp | 10 auto keepDims = model->addOperand(&type2);
16 model->setOperandValue(keepDims, keepDims_init, sizeof(int32_t) * 1);
17 model->addOperation(ANEURALNETWORKS_MEAN, {input, axis, keepDims}, {output});
|
| mean_float_2.model.cpp | 10 auto keepDims = model->addOperand(&type2);
16 model->setOperandValue(keepDims, keepDims_init, sizeof(int32_t) * 1);
17 model->addOperation(ANEURALNETWORKS_MEAN, {input, axis, keepDims}, {output});
|
| mean_float_2_relaxed.model.cpp | 10 auto keepDims = model->addOperand(&type2);
16 model->setOperandValue(keepDims, keepDims_init, sizeof(int32_t) * 1);
17 model->addOperation(ANEURALNETWORKS_MEAN, {input, axis, keepDims}, {output});
|
| mean_quant8_1.model.cpp | 10 auto keepDims = model->addOperand(&type2);
16 model->setOperandValue(keepDims, keepDims_init, sizeof(int32_t) * 1);
17 model->addOperation(ANEURALNETWORKS_MEAN, {input, axis, keepDims}, {output});
|
| mean_quant8_2.model.cpp | 10 auto keepDims = model->addOperand(&type2);
16 model->setOperandValue(keepDims, keepDims_init, sizeof(int32_t) * 1);
17 model->addOperation(ANEURALNETWORKS_MEAN, {input, axis, keepDims}, {output});
|
| mean_relaxed.model.cpp | 10 auto keepDims = model->addOperand(&type2);
16 model->setOperandValue(keepDims, keepDims_init, sizeof(int32_t) * 1);
17 model->addOperation(ANEURALNETWORKS_MEAN, {input, axis, keepDims}, {output});
|
| /frameworks/ml/nn/common/operations/ |
| SimpleMath.cpp | 280 const int32_t* axis, const Shape& axisShape, bool keepDims,
298 axis, axisSize, keepDims, scratchBuffer, resolvedAxis);
307 axis, axisSize, keepDims, scratchBuffer, resolvedAxis);
|
| /frameworks/ml/nn/common/ |
| CpuExecutor.cpp | [all...] |
