diff options
Diffstat (limited to 'ethosu/vela/graph_optimiser.py')
| -rw-r--r-- | ethosu/vela/graph_optimiser.py | 18 |
1 files changed, 10 insertions, 8 deletions
diff --git a/ethosu/vela/graph_optimiser.py b/ethosu/vela/graph_optimiser.py index 8a393a2e..cd4ac63e 100644 --- a/ethosu/vela/graph_optimiser.py +++ b/ethosu/vela/graph_optimiser.py @@ -131,6 +131,7 @@ def calc_padding_and_skirt(padding_type, kernel_size, stride, input_dims): skirt = (top_pad, left_pad, ypad - top_pad, xpad - left_pad) return padding, skirt + def calc_upscaled_padding_and_skirt(padding_type, kernel_size, stride, input_dims): upscaled_shape = [input_dims[0], input_dims[1] * stride[1], input_dims[2] * stride[2], input_dims[3]] ypad = needed_total_padding(int(upscaled_shape[1]), int(stride[1]), int(kernel_size[0])) @@ -174,7 +175,7 @@ def fixup_conv2d_backprop(op, arch): op.inputs.append(scale_tens) # Update strides - op.attrs.update( {"stride_w": 1, "stride_h": 1, "strides": (1,1,1,1)} ) + op.attrs.update({"stride_w": 1, "stride_h": 1, "strides": (1, 1, 1, 1)}) return op @@ -331,11 +332,15 @@ def add_padding_fields(op, arch): raise UnsupportedFeatureError("Unknown operation that uses padding: {}".format(op.type)) if op.type == "Conv2DBackpropInputSwitchedBias": - padding, skirt = calc_upscaled_padding_and_skirt(op.attrs["padding"], kernel_size, op.attrs["strides"], input_shape) + padding, skirt = calc_upscaled_padding_and_skirt( + op.attrs["padding"], kernel_size, op.attrs["strides"], input_shape + ) else: dilation_h, dilation_w = op.get_dilation_h_w() dilated_kernel_size = [dilation_h * (kernel_size[0] - 1) + 1, dilation_w * (kernel_size[1] - 1) + 1] - padding, skirt = calc_padding_and_skirt(op.attrs["padding"], dilated_kernel_size, op.attrs["strides"], input_shape) + padding, skirt = calc_padding_and_skirt( + op.attrs["padding"], dilated_kernel_size, op.attrs["strides"], input_shape + ) op.attrs["explicit_padding"] = padding op.attrs["skirt"] = skirt @@ -540,7 +545,7 @@ def convert_mul_max_to_abs_or_lrelu(op, arch): def add_attrs_to_resizebilinear(op, arch): - if op.type == 'ResizeBilinear' and op.run_on_npu: + if op.type == "ResizeBilinear" and op.run_on_npu: input_tensor = op.inputs[0] upscaled_shape = [input_tensor.shape[1] * 2, input_tensor.shape[2] * 2] out_shape = op.outputs[0].shape[1:3] @@ -556,10 +561,7 @@ def add_attrs_to_resizebilinear(op, arch): # If this exception is raised, something is wrong with the supported op check raise UnsupportedFeatureError("Unsupported upscaling factor") input_tensor.resampling_mode = resampling_mode.NEAREST - op.attrs.update({ - 'strides': (1, 1, 1, 1), - 'ksize': (1, 2, 2, 1), - }) + op.attrs.update({"strides": (1, 1, 1, 1), "ksize": (1, 2, 2, 1)}) return op |