diff options
Diffstat (limited to 'ethosu/vela/operation_util.py')
| -rw-r--r-- | ethosu/vela/operation_util.py | 85 |
1 files changed, 67 insertions, 18 deletions
diff --git a/ethosu/vela/operation_util.py b/ethosu/vela/operation_util.py index 7015b799..e7e4bbbc 100644 --- a/ethosu/vela/operation_util.py +++ b/ethosu/vela/operation_util.py @@ -24,7 +24,7 @@ from .operation import ActivationFunction from .operation import Op from .operation import Operation from .operation import Padding -from .tensor import create_reshape_tensor +from .shape4d import Shape4D from .tensor import QuantizationParameters from .tensor import Tensor @@ -44,12 +44,17 @@ def create_avgpool_nop(name: str) -> Operation: def create_depthwise_maxpool( - name: str, ifm: Tensor, quantization: QuantizationParameters, activation: Optional[ActivationFunction] = None + name: str, + ifm: Tensor, + inp_shape: Shape4D, + quantization: QuantizationParameters, + activation: Optional[ActivationFunction] = None, ) -> Operation: op = Operation(Op.MaxPool, name) - height = ifm.shape[1] * ifm.shape[2] - width = ifm.shape[3] - ifm_shape = [1, height, width, 1] + height = inp_shape.height * inp_shape.width + width = inp_shape.depth + ifm_shape = Shape4D([1, height, width, 1]) + op.attrs["padding"] = Padding.VALID op.attrs["stride_w"] = 1 op.attrs["stride_h"] = 1 @@ -58,11 +63,14 @@ def create_depthwise_maxpool( op.attrs["strides"] = [1, op.attrs["stride_h"], op.attrs["stride_w"], 1] op.attrs["ksize"] = [1, op.attrs["filter_height"], op.attrs["filter_width"], 1] op.activation = activation - op.inputs = [create_reshape_tensor(ifm, ifm_shape)] + op.inputs = [ifm] ofm = Tensor([1, height, 1, 1], ifm.dtype, op.name + "_tens0") ofm.quantization = quantization op.set_output_tensor(ofm) - op.set_ifm_ofm_shapes() + op.ifm_shapes.append(ifm_shape) + op.ofm_shapes.append(Shape4D(ofm.shape)) + op.ifm.avoid_NHCWB16 = True + op.ofm.avoid_NHCWB16 = True return op @@ -95,8 +103,12 @@ def create_add( activation: Optional[ActivationFunction] = None, dtype: Optional[DataType] = None, attrs: Optional[dict] = None, + ifm_shape: Optional[Shape4D] = None, + ifm2_shape: Optional[Shape4D] = None, ) -> Operation: - return create_binary_elementwise(Op.Add, name, ifm, ifm2, quantization, activation, dtype, attrs) + return create_binary_elementwise( + Op.Add, name, ifm, ifm2, quantization, activation, dtype, attrs, ifm_shape, ifm2_shape + ) def create_rescale_add( @@ -108,8 +120,12 @@ def create_rescale_add( activation: Optional[ActivationFunction] = None, dtype: Optional[DataType] = None, attrs: Optional[dict] = None, + ifm_shape: Optional[Shape4D] = None, + ifm2_shape: Optional[Shape4D] = None, ) -> Operation: - op = create_binary_elementwise(Op.RescaleAdd, name, ifm, ifm2, quantization, activation, dtype, attrs) + op = create_binary_elementwise( + Op.RescaleAdd, name, ifm, ifm2, quantization, activation, dtype, attrs, ifm_shape, ifm2_shape + ) op.rescale = rescale return op @@ -121,8 +137,9 @@ def create_clz( activation: Optional[ActivationFunction] = None, dtype: Optional[DataType] = None, attrs: Optional[dict] = None, + ifm_shape: Optional[Shape4D] = None, ) -> Operation: - return create_unary_elementwise(Op.CLZ, name, ifm, quantization, activation, dtype, attrs) + return create_unary_elementwise(Op.CLZ, name, ifm, quantization, activation, dtype, attrs, ifm_shape) def create_mul( @@ -133,8 +150,12 @@ def create_mul( activation: Optional[ActivationFunction] = None, dtype: Optional[DataType] = None, attrs: Optional[dict] = None, + ifm_shape: Optional[Shape4D] = None, + ifm2_shape: Optional[Shape4D] = None, ) -> Operation: - return create_binary_elementwise(Op.Mul, name, ifm, ifm2, quantization, activation, dtype, attrs) + return create_binary_elementwise( + Op.Mul, name, ifm, ifm2, quantization, activation, dtype, attrs, ifm_shape, ifm2_shape + ) def create_shl( @@ -145,8 +166,12 @@ def create_shl( activation: Optional[ActivationFunction] = None, dtype: Optional[DataType] = None, attrs: Optional[dict] = None, + ifm_shape: Optional[Shape4D] = None, + ifm2_shape: Optional[Shape4D] = None, ) -> Operation: - return create_binary_elementwise(Op.SHL, name, ifm, ifm2, quantization, activation, dtype, attrs) + return create_binary_elementwise( + Op.SHL, name, ifm, ifm2, quantization, activation, dtype, attrs, ifm_shape, ifm2_shape + ) def create_shr( @@ -157,8 +182,12 @@ def create_shr( activation: Optional[ActivationFunction] = None, dtype: Optional[DataType] = None, attrs: Optional[dict] = None, + ifm_shape: Optional[Shape4D] = None, + ifm2_shape: Optional[Shape4D] = None, ) -> Operation: - return create_binary_elementwise(Op.SHR, name, ifm, ifm2, quantization, activation, dtype, attrs) + return create_binary_elementwise( + Op.SHR, name, ifm, ifm2, quantization, activation, dtype, attrs, ifm_shape, ifm2_shape + ) def create_sub( @@ -169,8 +198,12 @@ def create_sub( activation: Optional[ActivationFunction] = None, dtype: Optional[DataType] = None, attrs: Optional[dict] = None, + ifm_shape: Optional[Shape4D] = None, + ifm2_shape: Optional[Shape4D] = None, ) -> Operation: - return create_binary_elementwise(Op.Sub, name, ifm, ifm2, quantization, activation, dtype, attrs) + return create_binary_elementwise( + Op.Sub, name, ifm, ifm2, quantization, activation, dtype, attrs, ifm_shape, ifm2_shape + ) def create_unary_elementwise( @@ -181,8 +214,9 @@ def create_unary_elementwise( activation: Optional[ActivationFunction] = None, dtype: Optional[DataType] = None, attrs: Optional[dict] = None, + ifm_shape: Optional[Shape4D] = None, ) -> Operation: - return create_binary_elementwise(op_type, name, ifm, None, quantization, activation, dtype, attrs) + return create_binary_elementwise(op_type, name, ifm, None, quantization, activation, dtype, attrs, ifm_shape, None) def create_binary_elementwise( @@ -194,19 +228,34 @@ def create_binary_elementwise( activation: Optional[ActivationFunction] = None, dtype: Optional[DataType] = None, attrs: Optional[dict] = None, + ifm_shape: Optional[Shape4D] = None, + ifm2_shape: Optional[Shape4D] = None, ) -> Operation: + if ifm_shape is None: + ifm_shape = Shape4D(ifm.shape) op = Operation(op_type, name) op.add_input_tensor(ifm) + op.ifm_shapes.append(ifm_shape) if ifm2: op.add_input_tensor(ifm2) + if ifm2_shape is None: + ifm2_shape = Shape4D(ifm2.shape) + op.ifm_shapes.append(ifm2_shape) op.activation = activation if not dtype: dtype = ifm.dtype if attrs: op.attrs.update(attrs) - ofm_shape = ifm.shape if ifm2 is None or ifm_ifm2_correct_order(ifm.shape, ifm2.shape) else ifm2.shape - ofm = Tensor(ofm_shape, dtype, f"{op.name}_tens0") + + if ifm2 is None: + ofm_shape = ifm_shape + else: + in_shape = [] if ifm.shape == [] else ifm_shape.as_list() + in2_shape = [] if ifm2.shape == [] else ifm2_shape.as_list() + ofm_shape = ifm_shape if ifm_ifm2_correct_order(in_shape, in2_shape) else ifm2_shape + + ofm = Tensor(ofm_shape.as_list(), dtype, f"{op.name}_tens0") ofm.quantization = quantization op.set_output_tensor(ofm) - op.set_ifm_ofm_shapes() + op.ofm_shapes.append(ofm_shape) return op |