pytorch · jirioc · Dec 19, 2025
@@ -56,7 +56,7 @@ class EdgeProgramToIRConverter:
     """
 
     _default_conversion_config = ConversionConfig()
-    _default_target_spec = NeutronTargetSpec("imxrt700", "SDK_25_09")
+    _default_target_spec = NeutronTargetSpec("imxrt700", "SDK_25_12")
     _default_delegation_options = CustomDelegationOptions()
 
     def convert_program(

@@ -28,7 +28,7 @@ class NeutronConverterManager:
 
     def __init__(
         self,
-        neutron_converter_flavor: str = "SDK_25_09",
+        neutron_converter_flavor: str = "SDK_25_12",
     ):
 
         neutron_converter_modules = [

@@ -67,7 +67,7 @@ def neutron_compile_spec(
         Args:
             config: Neutron accelerator configuration, e.g. "imxrt700"
             neutron_converter_flavor: Flavor of the neutron-converter module to use. Neutron-converter module named "
-             "'neutron_converter_SDK_25_09' has flavor 'SDK_25_09'.
+             "'neutron_converter_SDK_25_12' has flavor 'SDK_25_12'.
             extra_flags: Extra flags for the Neutron compiler
             operators_not_to_delegate: List of operators that should not be delegated
             use_neutron_for_format_conversion: If True, the EdgeProgramToIRConverter will insert `Transpose` ops to

@@ -1,2 +1,2 @@
 --index-url https://eiq.nxp.com/repository
-neutron_converter_SDK_25_09
+neutron_converter_SDK_25_12
@@ -38,7 +38,7 @@
 from torch.export import export
 from torchao.quantization.pt2e.quantizer import Quantizer
 
-neutron_converter_flavor = "SDK_25_09"
+neutron_converter_flavor = "SDK_25_12"
 neutron_target_spec = NeutronTargetSpec(
     target="imxrt700", neutron_converter_flavor=neutron_converter_flavor
 )

@@ -363,7 +363,7 @@ def test_cat__same_shapes_converter_padding_last_dimension(use_qat):
         CatModule(2),
         [input_shape, input_shape],
         target=target,
-        neutron_converter_flavor="SDK_25_09",
+        neutron_converter_flavor="SDK_25_12",
         custom_delegation_options=CustomDelegationOptions(),
         use_qat=use_qat,
     ).exported_program()
@@ -385,7 +385,7 @@ def test_cat__same_shapes__channels_first__padding_channels(use_qat):
         CatConvModule(1),
         [input_shape, input_shape],
         target=target,
-        neutron_converter_flavor="SDK_25_09",
+        neutron_converter_flavor="SDK_25_12",
         custom_delegation_options=CustomDelegationOptions(),
         use_qat=use_qat,
     ).exported_program()

@@ -319,7 +319,7 @@ def test_remove_additional_quantize_dequantize_nodes_pass(self):
 
         edge_program_manager = edge_program_manager.transform(NeutronEdgePassManager())
 
-        compile_spec = generate_neutron_compile_spec(target, "SDK_25_09")
+        compile_spec = generate_neutron_compile_spec(target, "SDK_25_12")
         partitioner = NeutronPartitioner(
             compile_spec, neutron_target_spec, custom_delegation_options
         )

@@ -1,4 +1,4 @@
-# Copyright 2024 NXP
+# Copyright 2024-2025 NXP
 #
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
@@ -165,7 +165,7 @@ 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()
+    num_macs = NeutronTargetSpec("imxrt700", "SDK_25_12").get_num_macs()
     model = Conv2dModule(
         in_channels=num_macs, out_channels=num_macs, padding=1, stride=1
     )
@@ -222,7 +222,7 @@ def test_delegating_format_related_transpose_operators__supported_case(mocker):
 def test_delegating_format_related_transpose_operators__supported_output__unsupported_input(
     mocker,
 ):
-    num_macs = NeutronTargetSpec("imxrt700", "SDK_25_09").get_num_macs()
+    num_macs = NeutronTargetSpec("imxrt700", "SDK_25_12").get_num_macs()
     model = Conv2dModule(
         in_channels=num_macs,
         out_channels=num_macs,  # The output `Transpose` will be supported.
@@ -278,7 +278,7 @@ def test_delegating_format_related_transpose_operators__supported_output__unsupp
 def test_delegating_format_related_transpose_operators__supported_input__unsupported_output(
     mocker,
 ):
-    num_macs = NeutronTargetSpec("imxrt700", "SDK_25_09").get_num_macs()
+    num_macs = NeutronTargetSpec("imxrt700", "SDK_25_12").get_num_macs()
     model = Conv2dModule(
         in_channels=num_macs,
         out_channels=3,  # The output `Transpose` will NOT be supported.

@@ -56,7 +56,7 @@ def _quantize_and_lower_module(
         edge_compile_config=edge_compile_config,
     )
 
-    compile_spec = generate_neutron_compile_spec(target, "SDK_25_09")
+    compile_spec = generate_neutron_compile_spec(target, "SDK_25_12")
     partitioner = NeutronPartitioner(compile_spec, neutron_target_spec)
     return edge_program_manager.to_backend(partitioner)
 

@@ -23,11 +23,11 @@ Among currently supported machine learning models are:
 ## Development Requirements
 
 - [MCUXpresso IDE](https://www.nxp.com/design/design-center/software/development-software/mcuxpresso-software-and-tools-/mcuxpresso-integrated-development-environment-ide:MCUXpresso-IDE) or [MCUXpresso Visual Studio Code extension](https://www.nxp.com/design/design-center/software/development-software/mcuxpresso-software-and-tools-/mcuxpresso-for-visual-studio-code:MCUXPRESSO-VSC)
-- [MCUXpresso SDK 25.06](https://mcuxpresso.nxp.com/mcuxsdk/25.06.00/html/index.html)
-- eIQ Neutron Converter for MCUXPresso SDK 25.06, what you can download from eIQ PyPI: 
+- [MCUXpresso SDK 25.12](https://mcuxpresso.nxp.com/mcuxsdk/25.12.00/html/index.html)
+- eIQ Neutron Converter for MCUXPresso SDK 25.12, what you can download from eIQ PyPI:
 
 ```commandline
-$ pip install --index-url https://eiq.nxp.com/repository neutron_converter_SDK_25_06
+$ pip install --index-url https://eiq.nxp.com/repository neutron_converter_SDK_25_12
 ```
 
 Instead of manually installing requirements, except MCUXpresso IDE and SDK, you can use the setup script: 

@@ -16,7 +16,7 @@ To generate the Compile Spec for Neutron backend, you can use the `generate_neut
 Following fields can be set:
 
 * `config` - NXP platform defining the Neutron NPU configuration, e.g. "imxrt700".
-* `neutron_converter_flavor` - Flavor of the neutron-converter module to use. Neutron-converter module named neutron_converter_SDK_25_06' has flavor 'SDK_25_06'. You shall set the flavour to the MCUXpresso SDK version you will use.
+* `neutron_converter_flavor` - Flavor of the neutron-converter module to use. Neutron-converter module named neutron_converter_SDK_25_12' has flavor 'SDK_25_12'. You shall set the flavour to the MCUXpresso SDK version you will use.
 * `extra_flags` - Extra flags for the Neutron compiler.
 * `operators_not_to_delegate` - List of operators that will not be delegated.
 

@@ -64,7 +64,7 @@ from torchao.quantization.pt2e.quantize_pt2e import convert_pt2e, prepare_pt2e
 model = models.mobilenetv2.mobilenet_v2(weights=MobileNet_V2_Weights.DEFAULT).eval()
 sample_inputs = (torch.randn(1, 3, 224, 224), )
 
-target_spec = NeutronTargetSpec(target="imxrt700", converter_flavor="SDK_25_09")
+target_spec = NeutronTargetSpec(target="imxrt700", converter_flavor="SDK_25_12")
 quantizer = NeutronQuantizer(neutron_target_spec) # (1)
 
 training_ep = torch.export.export(model, sample_inputs).module() # (2)
@@ -78,7 +78,7 @@ quantized_model = convert_pt2e(prepared_model) # (5)
 compile_spec = generate_neutron_compile_spec(
     "imxrt700",
     operators_not_to_delegate=None,
-    neutron_converter_flavor="SDK_25_06",
+    neutron_converter_flavor="SDK_25_12",
 )
 
 et_program = to_edge_transform_and_lower( # (6)
@@ -95,7 +95,7 @@ from executorch.backends.nxp.quantizer.utils import calibrate_and_quantize
 
 ...
 
-target_spec = NeutronTargetSpec(target="imxrt700", converter_flavor="SDK_25_09")
+target_spec = NeutronTargetSpec(target="imxrt700", converter_flavor="SDK_25_12")
 quantized_graph_module = calibrate_and_quantize(
     aten_model,
     calibration_inputs,

@@ -36,11 +36,11 @@ The steps are expected to be executed from the `executorch` root folder.
 1. Run the `aot_neutron_compile.py` example with the `cifar10` model 
     ```commandline
     $ python -m examples.nxp.aot_neutron_compile --quantize \
-        --delegate --neutron_converter_flavor SDK_25_09 -m cifar10 
+        --delegate --neutron_converter_flavor SDK_25_12 -m cifar10
     ```
 
 2. It will generate you `cifar10_nxp_delegate.pte` file which can be used with the MCUXpresso SDK `cifarnet_example` 
 project, presented [here](https://mcuxpresso.nxp.com/mcuxsdk/latest/html/middleware/eiq/executorch/docs/nxp/topics/example_applications.html#how-to-build-and-run-executorch-cifarnet-example).
 This project will guide you through the process of deploying your PTE model to the device.
 To get the MCUXpresso SDK follow this [guide](https://mcuxpresso.nxp.com/mcuxsdk/latest/html/middleware/eiq/executorch/docs/nxp/topics/getting_mcuxpresso.html),
-use the MCUXpresso SDK v25.09.00. 
+use the MCUXpresso SDK v25.12.00.
@@ -137,9 +137,9 @@ def get_model_and_inputs_from_name(model_name: str):
         "-c",
         "--neutron_converter_flavor",
         required=False,
-        default="SDK_25_09",
+        default="SDK_25_12",
         help="Flavor of installed neutron-converter module. Neutron-converter module named "
-        "'neutron_converter_SDK_25_09' has flavor 'SDK_25_09'.",
+        "'neutron_converter_SDK_25_12' has flavor 'SDK_25_12'.",
     )
     parser.add_argument(
         "-q",

@@ -13,6 +13,6 @@ cd $EXECUTORCH_DIR
 
 # Run the AoT example
 python -m examples.nxp.aot_neutron_compile --quantize \
-    --delegate --neutron_converter_flavor SDK_25_09 -m ${MODEL}
+    --delegate --neutron_converter_flavor SDK_25_12 -m ${MODEL}
 # verify file exists
 test -f ${MODEL}_nxp_delegate.pte
@@ -7,7 +7,7 @@
 set -u
 
 # Install neutron-converter
-pip install --index-url https://eiq.nxp.com/repository neutron_converter_SDK_25_09
+pip install --index-url https://eiq.nxp.com/repository neutron_converter_SDK_25_12
 
 # Get the directory of the current script
 SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"