diff options
| author | Fredrik Svedberg <fredrik.svedberg@arm.com> | 2020-09-29 10:00:39 +0200 |
|---|---|---|
| committer | patrik.gustavsson <patrik.gustavsson@arm.com> | 2020-09-30 07:52:39 +0000 |
| commit | 0f98b361288c71fca327969346db32de098c797b (patch) | |
| tree | 8b2905a6e763832a0029179d655c481b14e0a8a1 /ethosu/vela/tflite_reader.py | |
| parent | 0265f402c7ae1e875470298b4130fcc2f7ab4e23 (diff) | |
| download | ethos-u-vela-0f98b361288c71fca327969346db32de098c797b.tar.gz | |
[MLBEDSW-2802] Fix 5D tensor crash
Fixed crash in networks with 5D tensors.
Fixed crash for (int32) tensors without quantization.
Added validity checks for concatenation.
Moved unfusing of activation function from tflite_reader to graph_optimiser.
Signed-off-by: Fredrik Svedberg <fredrik.svedberg@arm.com>
Change-Id: Ib9ba8891dc95ef5491e15d0feedef44331a26393
Diffstat (limited to 'ethosu/vela/tflite_reader.py')
| -rw-r--r-- | ethosu/vela/tflite_reader.py | 17 |
1 files changed, 0 insertions, 17 deletions
diff --git a/ethosu/vela/tflite_reader.py b/ethosu/vela/tflite_reader.py index 7458b907..77cc7963 100644 --- a/ethosu/vela/tflite_reader.py +++ b/ethosu/vela/tflite_reader.py @@ -149,8 +149,6 @@ class TFLiteSubgraph: for out in op.outputs: out.ops = [op] - activation_function_to_split_out = None - if op_type.startswith("DepthwiseConv2d") or op_type.startswith("Conv2D"): if inputs[1].values is not None: inputs[1] = clone_and_reshape_tensor(inputs[1], (1, 2, 3, 0)) @@ -192,21 +190,6 @@ class TFLiteSubgraph: if "depth_multiplier" in op.attrs: op.attrs["channel_multiplier"] = op.attrs["depth_multiplier"] - if "fused_activation_function" in op.attrs: - if op_type in set(("ConcatTFLite",)): - act = op.attrs["fused_activation_function"] - del op.attrs["fused_activation_function"] - if act is not None: - activation_function_to_split_out = act - - if activation_function_to_split_out is not None: - act_op = Operation(activation_function_to_split_out, name + activation_function_to_split_out) - out_tens = op.outputs[0] - intermediate_tens = out_tens.clone("_act_intermediate") - act_op.set_output_tensor(out_tens) - intermediate_tens.ops = [op] - op.outputs[0] = intermediate_tens - act_op.inputs = [intermediate_tens] @staticmethod def len1_array_to_scalar(arr): |