diff options
Diffstat (limited to 'ethosu/vela/graph_optimiser.py')
| -rw-r--r-- | ethosu/vela/graph_optimiser.py | 22 |
1 files changed, 11 insertions, 11 deletions
diff --git a/ethosu/vela/graph_optimiser.py b/ethosu/vela/graph_optimiser.py index 15d13522..4806001f 100644 --- a/ethosu/vela/graph_optimiser.py +++ b/ethosu/vela/graph_optimiser.py @@ -35,6 +35,7 @@ from .operation import create_activation_function from .operation import NpuBlockType from .operation import Op from .operation import Operation +from .operation import Padding from .operation_util import create_avgpool_nop from .softmax import SoftMax from .tensor import check_quantized_tens_scaling_equal @@ -147,18 +148,18 @@ def needed_total_padding(input_size, stride, filter_size): def calc_padding_and_skirt(padding_type, kernel_size, stride, input_dims): ypad = needed_total_padding(int(input_dims[1]), int(stride[1]), int(kernel_size[0])) xpad = needed_total_padding(int(input_dims[2]), int(stride[2]), int(kernel_size[1])) - if padding_type == b"SAME": + if padding_type == Padding.SAME: left_pad = (xpad + 0) // 2 right_pad = (xpad + 1) // 2 top_pad = (ypad + 0) // 2 bottom_pad = (ypad + 1) // 2 - elif padding_type == b"VALID": + elif padding_type == Padding.VALID: left_pad = 0 right_pad = 0 top_pad = 0 bottom_pad = 0 else: - raise UnsupportedFeatureError(f"Unknown padding {padding_type.decode('utf-8')}") + raise UnsupportedFeatureError(f"Unknown padding") padding = (top_pad, left_pad, bottom_pad, right_pad) skirt = (top_pad, left_pad, ypad - top_pad, xpad - left_pad) return padding, skirt @@ -166,21 +167,20 @@ def calc_padding_and_skirt(padding_type, kernel_size, stride, input_dims): def calc_upscaled_padding_and_skirt(padding_type, kernel_size, stride, input_dims, upscaling_factor): kernel_height, kernel_width = kernel_size[0], kernel_size[1] - if padding_type == b"SAME": + if padding_type == Padding.SAME: ypad = needed_total_padding(int(input_dims[1]) * upscaling_factor, int(stride[1]), int(kernel_height)) xpad = needed_total_padding(int(input_dims[2]) * upscaling_factor, int(stride[2]), int(kernel_width)) right_pad = max(((xpad + 1) // upscaling_factor) - 1, 0) bottom_pad = max(((ypad + 1) // upscaling_factor) - 1, 0) left_pad = max(kernel_width - 1 - right_pad, 0) top_pad = max(kernel_height - 1 - bottom_pad, 0) - elif padding_type == b"VALID": + elif padding_type == Padding.VALID: right_pad = max(kernel_width - 2, 0) bottom_pad = max(kernel_height - 2, 0) left_pad = kernel_width - 1 top_pad = kernel_height - 1 else: - raise UnsupportedFeatureError(f"Unknown padding {padding_type.decode('utf-8')}") - + raise UnsupportedFeatureError(f"Unknown padding") padding = (top_pad, left_pad, bottom_pad, right_pad) skirt = padding return padding, skirt @@ -230,10 +230,10 @@ def convert_resizebilinear_to_2x2_pool(op): op.attrs.update({"strides": (1, 1, 1, 1), "ksize": (1, 2, 2, 1)}) if op.attrs["align_corners"]: shape_modifier = 1 - op.attrs["padding"] = b"VALID" + op.attrs["padding"] = Padding.VALID else: shape_modifier = 0 - op.attrs["padding"] = b"SAME" + op.attrs["padding"] = Padding.SAME op.inputs[0].resampling_mode = resampling_mode.NEAREST upscaled_shape = np.array(op.inputs[0].shape[1:3]) @@ -1034,11 +1034,11 @@ def add_attrs_to_resizebilinear(op, arch, nng): if not op.attrs["align_corners"] and out_shape == upscaled_shape: # this means the output is supposed to be a x2 upscale, # so we need to do SAME padding - op.attrs["padding"] = b"SAME" + op.attrs["padding"] = Padding.SAME elif op.attrs["align_corners"] and out_shape == [upscaled_shape[0] - 1, upscaled_shape[1] - 1]: # here we can just run the avg pool without padding and # produce a (M * 2 - 1, N * 2 - 1) sized output - op.attrs["padding"] = b"VALID" + op.attrs["padding"] = Padding.VALID else: return op input_tensor.resampling_mode = resampling_mode.NEAREST |