NXP backend: Re-organize Neutron backend tests.

Author: MartinPavella

backends/nxp/tests/test_neutron_backend.py

@@ -3,17 +3,7 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
-import torch
-
-from executorch.backends.nxp.backend.edge_program_converter import (
-    EdgeProgramToIRConverter,
-)
-from executorch.backends.nxp.backend.ir.lib.tflite.BuiltinOptions import BuiltinOptions
-from executorch.backends.nxp.backend.ir.lib.tflite.Model import Model
-from executorch.backends.nxp.backend.neutron_target_spec import NeutronTargetSpec
-from executorch.backends.nxp.nxp_backend import PayloadComposer
 from executorch.backends.nxp.tests.executorch_pipeline import to_quantized_edge_program
-from executorch.backends.nxp.tests.executors import graph_contains_any_of_ops
 from executorch.backends.nxp.tests.models import Conv2dModule, LinearSoftmaxModule
 
 
@@ -65,217 +55,3 @@ def test_neutron_backend__linear_softmax_model__payload_header_formatless():
     assert payload[6] == 0x0  # Map 0-th Neutron output to 0-th model output
     assert all(byte == 0x0 for byte in payload[7:16])  # Aligned to 16 bytes
     assert payload[17] != 0x0  # Followed by non-zero content
-
-
-def test_delegating_format_related_transpose_operators__unsupported_shapes(mocker):
-    # This test focuses on the case when Neutron would not support the inserted Transpose operators, so they are not
-    #  inserted, so the runtime will permute the data.
-
-    # Make sure none of the dimensions are multiples of `num_macs` (8), for proper testing.
-    model = Conv2dModule(in_channels=3, out_channels=3, padding=1, stride=1)
-    input_shape = (1, 3, 3, 3)
-
-    converter_spy = mocker.spy(EdgeProgramToIRConverter, "convert_program")
-    payload_header_spy = mocker.spy(PayloadComposer, "_create_payload_header")
-    edge_program = to_quantized_edge_program(
-        model,
-        input_shape,
-        use_neutron_for_format_conversion=True,  # Make sure the IR converter inserts the extra `Transpose` operators.
-    ).exported_program()
-
-    # Make sure the edge_program only contains the 1 delegate call.
-    nodes = list(edge_program.graph.nodes)
-    assert len(nodes) == 7
-    assert "call_delegate" in nodes[3].name
-    assert not graph_contains_any_of_ops(
-        edge_program.graph, [torch.ops.aten.convolution.default]
-    )
-    assert not graph_contains_any_of_ops(
-        edge_program.graph, [torch.ops.aten.permute_copy.default]
-    )
-
-    # Capture the converted IR model.
-    tflite_flatbuffers_model, _ = converter_spy.spy_return
-
-    # Make sure the `Transpose` ops are NOT in the IR model.
-    tflite_subgraph = Model.GetRootAs(tflite_flatbuffers_model).Subgraphs(0)
-    assert tflite_subgraph.OperatorsLength() == 2
-    assert (
-        tflite_subgraph.Operators(0).BuiltinOptionsType() == BuiltinOptions.PadV2Options
-    )
-    assert (
-        tflite_subgraph.Operators(1).BuiltinOptionsType()
-        == BuiltinOptions.Conv2DOptions
-    )
-
-    # Get the header of the payload for the delegated partition.
-    payload_header = payload_header_spy.spy_return
-    assert payload_header.size == 7
-    # the 4th and 5th bytes indicate the format. `1` means `channels_last`, which means the runtime will transpose the data.
-    assert all(payload_header[3:5] == [1, 1])  # [<input_byte>, <output_byte>]
-
-
-def test_delegating_format_related_transpose_operators__supported_case(mocker):
-    # Make sure the output channels (channels for the trailing Transpose), and the last input dimension (channels for
-    #  the leading Transpose) are multiples of `num_macs``.
-
-    num_macs = NeutronTargetSpec("imxrt700", "SDK_25_09").get_num_macs()
-    model = Conv2dModule(
-        in_channels=num_macs, out_channels=num_macs, padding=1, stride=1
-    )
-    input_shape = (1, num_macs, num_macs, num_macs)
-
-    converter_spy = mocker.spy(EdgeProgramToIRConverter, "convert_program")
-    payload_header_spy = mocker.spy(PayloadComposer, "_create_payload_header")
-    edge_program = to_quantized_edge_program(
-        model,
-        input_shape,
-        use_neutron_for_format_conversion=True,  # Make sure the IR converter inserts the extra `Transpose` operators.
-    ).exported_program()
-
-    # Make sure the edge_program only contains the 1 delegate call.
-    nodes = list(edge_program.graph.nodes)
-    assert len(nodes) == 7
-    assert "call_delegate" in nodes[3].name
-    assert not graph_contains_any_of_ops(
-        edge_program.graph, [torch.ops.aten.convolution.default]
-    )
-    assert not graph_contains_any_of_ops(
-        edge_program.graph, [torch.ops.aten.permute_copy.default]
-    )
-
-    # Capture the converted IR model.
-    tflite_flatbuffers_model, _ = converter_spy.spy_return
-
-    # Make sure the `Transpose` ops ARE in the IR model.
-    tflite_subgraph = Model.GetRootAs(tflite_flatbuffers_model).Subgraphs(0)
-    assert tflite_subgraph.OperatorsLength() == 4
-    assert (
-        tflite_subgraph.Operators(0).BuiltinOptionsType()
-        == BuiltinOptions.TransposeOptions
-    )
-    assert (
-        tflite_subgraph.Operators(1).BuiltinOptionsType() == BuiltinOptions.PadV2Options
-    )
-    assert (
-        tflite_subgraph.Operators(2).BuiltinOptionsType()
-        == BuiltinOptions.Conv2DOptions
-    )
-    assert (
-        tflite_subgraph.Operators(3).BuiltinOptionsType()
-        == BuiltinOptions.TransposeOptions
-    )
-
-    # Get the header of the payload for the delegated partition.
-    payload_header = payload_header_spy.spy_return
-    assert payload_header.size == 7
-    # the 4th and 5th bytes indicate the format. `0` means `channels_last`, which means the runtime will NOT transpose the data.
-    assert all(payload_header[3:5] == [0, 0])  # [<input_byte>, <output_byte>]
-
-
-def test_delegating_format_related_transpose_operators__supported_output__unsupported_input(
-    mocker,
-):
-    num_macs = NeutronTargetSpec("imxrt700", "SDK_25_09").get_num_macs()
-    model = Conv2dModule(
-        in_channels=num_macs,
-        out_channels=num_macs,  # The output `Transpose` will be supported.
-        padding=1,
-        stride=1,
-    )
-    input_shape = (1, num_macs, num_macs, 3)  # The input `Transpose` is not supported.
-
-    converter_spy = mocker.spy(EdgeProgramToIRConverter, "convert_program")
-    payload_header_spy = mocker.spy(PayloadComposer, "_create_payload_header")
-    edge_program = to_quantized_edge_program(
-        model,
-        input_shape,
-        use_neutron_for_format_conversion=True,  # Make sure the IR converter inserts the extra `Transpose` operators.
-    ).exported_program()
-
-    # Make sure the edge_program only contains the 1 delegate call.
-    nodes = list(edge_program.graph.nodes)
-    assert len(nodes) == 7
-    assert "call_delegate" in nodes[3].name
-    assert not graph_contains_any_of_ops(
-        edge_program.graph, [torch.ops.aten.convolution.default]
-    )
-    assert not graph_contains_any_of_ops(
-        edge_program.graph, [torch.ops.aten.permute_copy.default]
-    )
-
-    # Capture the converted IR model.
-    tflite_flatbuffers_model, _ = converter_spy.spy_return
-
-    # Make sure there is just the 1 `Transpose` in the model.
-    tflite_subgraph = Model.GetRootAs(tflite_flatbuffers_model).Subgraphs(0)
-    assert tflite_subgraph.OperatorsLength() == 3
-    assert (
-        tflite_subgraph.Operators(0).BuiltinOptionsType() == BuiltinOptions.PadV2Options
-    )
-    assert (
-        tflite_subgraph.Operators(1).BuiltinOptionsType()
-        == BuiltinOptions.Conv2DOptions
-    )
-    assert (
-        tflite_subgraph.Operators(2).BuiltinOptionsType()
-        == BuiltinOptions.TransposeOptions
-    )
-
-    # Get the header of the payload for the delegated partition.
-    payload_header = payload_header_spy.spy_return
-    assert payload_header.size == 7
-    # the 4th and 5th bytes indicate the format. `1` means `channels_last`, which means the runtime will transpose the data.
-    assert all(payload_header[3:5] == [1, 0])  # [<input_byte>, <output_byte>]
-
-
-def test_delegating_format_related_transpose_operators__supported_input__unsupported_output(
-    mocker,
-):
-    num_macs = NeutronTargetSpec("imxrt700", "SDK_25_09").get_num_macs()
-    model = Conv2dModule(
-        in_channels=num_macs,
-        out_channels=3,  # The output `Transpose` will NOT be supported.
-        stride=1,
-    )
-    input_shape = (1, num_macs, 3, num_macs)  # The input `Transpose` is supported.
-
-    converter_spy = mocker.spy(EdgeProgramToIRConverter, "convert_program")
-    payload_header_spy = mocker.spy(PayloadComposer, "_create_payload_header")
-    edge_program = to_quantized_edge_program(
-        model,
-        input_shape,
-        use_neutron_for_format_conversion=True,  # Make sure the IR converter inserts the extra `Transpose` operators.
-    ).exported_program()
-
-    # Make sure the edge_program only contains the 1 delegate call.
-    nodes = list(edge_program.graph.nodes)
-    assert len(nodes) == 7
-    assert "call_delegate" in nodes[3].name
-    assert not graph_contains_any_of_ops(
-        edge_program.graph, [torch.ops.aten.convolution.default]
-    )
-    assert not graph_contains_any_of_ops(
-        edge_program.graph, [torch.ops.aten.permute_copy.default]
-    )
-
-    # Capture the converted IR model.
-    tflite_flatbuffers_model, _ = converter_spy.spy_return
-
-    # Make sure there is just the 1 `Transpose` in the model.
-    tflite_subgraph = Model.GetRootAs(tflite_flatbuffers_model).Subgraphs(0)
-    assert tflite_subgraph.OperatorsLength() == 2
-    assert (
-        tflite_subgraph.Operators(0).BuiltinOptionsType()
-        == BuiltinOptions.TransposeOptions
-    )
-    assert (
-        tflite_subgraph.Operators(1).BuiltinOptionsType()
-        == BuiltinOptions.Conv2DOptions
-    )
-
-    # Get the header of the payload for the delegated partition.
-    payload_header = payload_header_spy.spy_return
-    assert payload_header.size == 7
-    # the 4th and 5th bytes indicate the format. `1` means `channels_last`, which means the runtime will transpose the data.
-    assert all(payload_header[3:5] == [0, 1])  # [<input_byte>, <output_byte>]