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author | Patrik Gustavsson <patrik.gustavsson@arm.com> | 2021-01-29 11:51:31 +0100 |
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committer | Patrik Gustavsson <patrik.gustavsson@arm.com> | 2021-01-29 16:05:03 +0100 |
commit | 2c2522dd44229a03d3d778cd239478fedc19ee57 (patch) | |
tree | 610bd611f9783f71cf79f4c2e8466789cacfd429 /ethosu/vela/graph_optimiser.py | |
parent | 7bada4039d01836c995a12251034777055e1848a (diff) | |
download | ethos-u-vela-2c2522dd44229a03d3d778cd239478fedc19ee57.tar.gz |
MLBEDSW-3772 Fix FC with changed inp shape
When FC input is fixed by changing ifm_shape,
avoid_NHCWB16 must be set to ifm.
-Fixed issue with ResizeBilinear
-Changed to post order for concat ops in graph optimisation
Signed-off-by: Patrik Gustavsson <patrik.gustavsson@arm.com>
Change-Id: Ie0c6a86637c210c0833ae9b2f8e7c494c5d4f66e
Diffstat (limited to 'ethosu/vela/graph_optimiser.py')
-rw-r--r-- | ethosu/vela/graph_optimiser.py | 26 |
1 files changed, 20 insertions, 6 deletions
diff --git a/ethosu/vela/graph_optimiser.py b/ethosu/vela/graph_optimiser.py index f1b2d35c..ab4d916e 100644 --- a/ethosu/vela/graph_optimiser.py +++ b/ethosu/vela/graph_optimiser.py @@ -59,7 +59,7 @@ def remove_passthrough_tensor(tens, arch, nng): return tens -def rewrite_concat_ops(op, arch, nng): +def rewrite_concat_ops(op, arch): if not op.run_on_npu or not op.type.is_concat_op(): return op @@ -283,8 +283,8 @@ def convert_resizebilinear_to_2x2_pool(op): op.attrs["padding"] = Padding.SAME op.inputs[0].resampling_mode = resampling_mode.NEAREST - upscaled_shape = op.ifm_shape[0].get_hw_as_list() - out_shape = op.ofm_shape[0].get_hw_as_list() + upscaled_shape = np.array(op.ifm_shapes[0].get_hw_as_list()) + out_shape = np.array(op.ofm_shapes[0].get_hw_as_list()) if (upscaled_shape == upscaled_shape * 2 - shape_modifier).all(): return op @@ -346,6 +346,20 @@ def convert_nop_split_to_identity(op, arch, nng): return op +def rewrite_fully_connected_input(op, arch, nng): + if op.type == Op.FullyConnected: + n_in_elems = op.weights.shape[-2] + elms = op.ifm.elements() + batch_size = elms // n_in_elems + assert batch_size * n_in_elems == elms + + if op.ifm.shape != [batch_size, n_in_elems]: + op.ifm.avoid_NHCWB16 = True + + op.ifm_shapes[0] = Shape4D([batch_size, 1, 1, n_in_elems]) + return op + + def convert_batched_fc_shape(op, arch, nng): if op.type == Op.FullyConnected: # Check if the first dimension indicates batching @@ -1199,9 +1213,8 @@ def optimise_graph_a(nng, arch, verbose_graph=False): # Handle Concat Ops for idx, sg in enumerate(nng.subgraphs): # rewrite graph pass - nng.subgraphs[idx] = rewrite_graph.rewrite_graph_pre_order( - nng, sg, arch, [], [rewrite_concat_ops], rewrite_unsupported=False, - ) + rewrite_graph.visit_graph_post_order(sg.output_tensors, arch, [], [rewrite_concat_ops]) + sg.refresh_after_modification() # Handle Split Ops for idx, sg in enumerate(nng.subgraphs): @@ -1232,6 +1245,7 @@ def optimise_graph_a(nng, arch, verbose_graph=False): convert_conv_to_fc, convert_softmax, optimise_strided_conv, + rewrite_fully_connected_input, convert_batched_fc_shape, fixup_conv2d_backprop, fixup_relus_with_differing_ifm_ofm_scaling, |