diff options
| -rw-r--r-- | ethosu/vela/live_range.py | 2 | ||||
| -rw-r--r-- | ethosu/vela/mark_tensors.py | 4 | ||||
| -rw-r--r-- | ethosu/vela/nn_graph.py | 6 | ||||
| -rw-r--r-- | ethosu/vela/pass_packing.py | 15 | ||||
| -rw-r--r-- | ethosu/vela/tensor.py | 11 | ||||
| -rw-r--r-- | ethosu/vela/tflite_reader.py | 26 | ||||
| -rw-r--r-- | ethosu/vela/tflite_writer.py | 13 |
7 files changed, 67 insertions, 10 deletions
diff --git a/ethosu/vela/live_range.py b/ethosu/vela/live_range.py index b18afecc..6a2a04ac 100644 --- a/ethosu/vela/live_range.py +++ b/ethosu/vela/live_range.py @@ -155,6 +155,8 @@ class LiveRangeGraph: def tensor_should_be_ignored(tens, target_mem_area, target_mem_type_set): + if tens.purpose == TensorPurpose.Virtual: + return True if target_mem_area is None or target_mem_type_set is None: return False if tens.mem_area != target_mem_area or tens.mem_type not in target_mem_type_set: diff --git a/ethosu/vela/mark_tensors.py b/ethosu/vela/mark_tensors.py index 64cc7883..4b5bf1dc 100644 --- a/ethosu/vela/mark_tensors.py +++ b/ethosu/vela/mark_tensors.py @@ -1,4 +1,4 @@ -# SPDX-FileCopyrightText: Copyright 2020-2021 Arm Limited and/or its affiliates <open-source-office@arm.com> +# SPDX-FileCopyrightText: Copyright 2020-2023 Arm Limited and/or its affiliates <open-source-office@arm.com> # # SPDX-License-Identifier: Apache-2.0 # @@ -41,6 +41,8 @@ def mark_purpose(tens, arch, purpose): # Sets tensor's purpose, format, mem_area and mem_type if tens.purpose == TensorPurpose.Unknown: tens.purpose = purpose + elif tens.purpose == TensorPurpose.Virtual: + return elif tens.purpose not in (purpose, TensorPurpose.LUT): assert 0, "Cannot resolve tensor purpose {} and {} for tensor {}".format(tens.purpose, purpose, tens) diff --git a/ethosu/vela/nn_graph.py b/ethosu/vela/nn_graph.py index 846632df..a43aac2a 100644 --- a/ethosu/vela/nn_graph.py +++ b/ethosu/vela/nn_graph.py @@ -149,7 +149,11 @@ class Subgraph: def __init__(self, name="<unnamed>", placement=PassPlacement.Cpu): self.output_tensors = [] self.input_tensors = [] - self.original_inputs = [] # Preserve the original input order + # Preserve the original input order + self.original_inputs = [] + # Attach virtual outputs to resource variables op + # in order to be able to traverse the graph correctly + self.virtual_outputs = [] self.passes = [] self.cascaded_passes = [] self.name = name diff --git a/ethosu/vela/pass_packing.py b/ethosu/vela/pass_packing.py index 5c0d8ebe..6049366f 100644 --- a/ethosu/vela/pass_packing.py +++ b/ethosu/vela/pass_packing.py @@ -1,4 +1,4 @@ -# SPDX-FileCopyrightText: Copyright 2020-2022 Arm Limited and/or its affiliates <open-source-office@arm.com> +# SPDX-FileCopyrightText: Copyright 2020-2023 Arm Limited and/or its affiliates <open-source-office@arm.com> # # SPDX-License-Identifier: Apache-2.0 # @@ -469,6 +469,8 @@ def pack_into_passes(nng, arch, verbose_packing=False): # # 1) CPU passes that only depends on sg.input_tensor can be # moved to the top of the list. + # ResourceVariables ops like VarHandle, ReadVariable, CallOnce + # can also be moved to the top of list. # # 2) A CPU pass X is allowed to be grouped together with CPU pass Y # if there is no NPU pass between pass X and pass Y that depends @@ -487,17 +489,20 @@ def pack_into_passes(nng, arch, verbose_packing=False): pass_list_top.insert(0, ps) continue - if ( - ps.placement == PassPlacement.Cpu - and ps.ops[0].ifm in sg.input_tensors + if ps.placement == PassPlacement.Cpu and ( + ps.ops[0].ifm in sg.input_tensors and (ps.ops[0].ifm2 in sg.input_tensors or ps.ops[0].ifm2 is None) + or (ps.ops[0].type in (Op.VarHandle, Op.ReadVariable, Op.CallOnce)) ): - # This CPU pass only depends on sg.input_tensors + # This CPU pass only depends on sg.input_tensors or resource variable pass_list_top.append(ps) else: # Add pass to the list that will be sorted in the next step pass_list.append(ps) + # Sort ops by op_index (same call order as in the original graph) + pass_list_top = sorted(pass_list_top, key=lambda ps: -1 if ps.ops[0].op_index is None else ps.ops[0].op_index) + # Sort the rest of the list based on critera 2. # Search from bottom of list and when a CPU pass is found # search forward in the list and see if it is possible to join another CPU pass. diff --git a/ethosu/vela/tensor.py b/ethosu/vela/tensor.py index 6a95bad4..008cd05e 100644 --- a/ethosu/vela/tensor.py +++ b/ethosu/vela/tensor.py @@ -114,7 +114,8 @@ class TensorPurpose(enum.IntFlag): ScratchFast = 4 LUT = 5 FSBias = 6 - Size = 7 + Virtual = 7 + Size = 8 def display_name(self) -> str: return ("Unknown", "Weights", "FeatureMap", "Scratch", "ScratchFast", "LUT", "FastStorageBias", "Size")[ @@ -297,6 +298,14 @@ class QuantizationParameters: return False +def create_virtual_tensor( + name: str, +): + virtual_tensor = Tensor([], DataType.int8, name) + virtual_tensor.purpose = TensorPurpose.Virtual + return virtual_tensor + + def create_const_tensor( name: str, shape: Shape, diff --git a/ethosu/vela/tflite_reader.py b/ethosu/vela/tflite_reader.py index 80f36457..2325ff65 100644 --- a/ethosu/vela/tflite_reader.py +++ b/ethosu/vela/tflite_reader.py @@ -1,4 +1,4 @@ -# SPDX-FileCopyrightText: Copyright 2020-2022 Arm Limited and/or its affiliates <open-source-office@arm.com> +# SPDX-FileCopyrightText: Copyright 2020-2023 Arm Limited and/or its affiliates <open-source-office@arm.com> # # SPDX-License-Identifier: Apache-2.0 # @@ -32,6 +32,7 @@ from .reader_util import align_tensor_indices_to_nng from .reader_util import clone_and_reshape_tensor from .reader_util import decode_str from .reader_util import fixup_tensors +from .tensor import create_virtual_tensor from .tensor import QuantizationParameters from .tensor import Tensor from .tflite.BuiltinOperator import BuiltinOperator @@ -51,6 +52,7 @@ class TFLiteSubgraph: for idx in range(subgraph.TensorsLength()): self.tensors.append(self.parse_tensor(subgraph.Tensors(idx))) + self.virtual_outputs = [] for idx in range(subgraph.OperatorsLength()): self.parse_operator(idx, subgraph.Operators(idx)) @@ -58,6 +60,8 @@ class TFLiteSubgraph: self.inputs = self.get_tensors_from_indices_remove_duplicates(subgraph.InputsAsNumpy(), "input") fixup_tensors(self.inputs, self.tensors) + self.outputs.extend(self.virtual_outputs) + def get_tensors_from_indices_remove_duplicates(self, indices, warning_str): tensors = [] for idx in indices: @@ -131,6 +135,21 @@ class TFLiteSubgraph: for out in op.outputs: out.ops = [op] + if op_type in (Op.AssignVariable, Op.CallOnce): + # All graph traversals are based on depth-first and the starting + # points are the subgraph output tensors. Because of this, operators + # like AssignVariable and CallOnce will not be visit when the + # graph is traversed and the ops are never handled. In order to + # fix that, the code base will have to be changed in several places. + # Until then this workaround is applied. A virtual output is added + # both to the operator and to the subgraph. By doing this the full + # graph is traversed correctly. The tensor is not used for anything + # else. + op.name = f"{op_type}_{op_index}" + tens = create_virtual_tensor(op.name) + op.set_output_tensor(tens) + self.virtual_outputs.append(tens) + if op.type.is_depthwise_conv2d_op() or op.type.is_conv2d_op() or op.type == Op.FullyConnected: if inputs[1].values is not None: if op.type == Op.FullyConnected: @@ -156,6 +175,10 @@ class TFLiteSubgraph: self.graph.nng.subgraphs[cond_subgraph_index], self.graph.nng.subgraphs[body_subgraph_index], ) + if op_type == Op.CallOnce: + # Attach the actual nng subgraphs to the op + init_subgraph_index = op.attrs["init_subgraph_index"] + op.attrs["subgraph"] = (self.graph.nng.subgraphs[init_subgraph_index],) if op_type == Op.Reshape and "new_shape" not in op.attrs: # Reshape should have an attrib "new_shape" but if it is missing, add it based on the output shape @@ -250,6 +273,7 @@ class TFLiteGraph: sg.name = tflite_sg.name sg.original_inputs = tflite_sg.inputs # Preserve the original input order sg.output_tensors = tflite_sg.outputs + sg.virtual_outputs = tflite_sg.virtual_outputs parsing_step = "parsing metadata length" # Preserve the original metadata diff --git a/ethosu/vela/tflite_writer.py b/ethosu/vela/tflite_writer.py index e527cd4d..32982298 100644 --- a/ethosu/vela/tflite_writer.py +++ b/ethosu/vela/tflite_writer.py @@ -1,4 +1,4 @@ -# SPDX-FileCopyrightText: Copyright 2020-2022 Arm Limited and/or its affiliates <open-source-office@arm.com> +# SPDX-FileCopyrightText: Copyright 2020-2023 Arm Limited and/or its affiliates <open-source-office@arm.com> # # SPDX-License-Identifier: Apache-2.0 # @@ -321,6 +321,10 @@ class TFLiteSerialiser: attrs["dilation_w_factor"] = attrs["dilation"][2] if "channel_multiplier" in attrs: attrs["depth_multiplier"] = attrs["channel_multiplier"] + if "container" in attrs: + attrs["container"] = builder.CreateString(attrs["container"]) + if "shared_name" in attrs: + attrs["shared_name"] = builder.CreateString(attrs["shared_name"]) attrs["fused_activation_function"] = op.activation.op_type if op.activation is not None else None builtin_opt_offset, custom_opt_offset = opt_serializer.serialize(builder, attrs) @@ -362,6 +366,13 @@ class TFLiteSerialiser: # to an op. tensor_set = set(sg.original_inputs) + # Remove any virtual outputs since they are only used internally when + # traversing the graph. + for tens in sg.virtual_outputs: + tens.ops[0].outputs = [] + if tens in sg.output_tensors: + sg.output_tensors.remove(tens) + # Add the tensors from all valid ops, as well as the tensors from placeholder ops # This allows us to serialise tensors which arent attached to any specific ops, # e.g. due to an empty graph containing no ops |