From 17813ba5be09f0e11fc0748afa4ccf2da02881b6 Mon Sep 17 00:00:00 2001
From: Madeleine Dunn <madeleine.dunn@arm.com>
Date: Mon, 13 Nov 2023 15:40:21 +0000
Subject: feat: Implement fp32 sparsity 2:4 rewrite

- Update the existing placeholder with code to prune the given model

Resolves: MLIA-1002

Signed-off-by: Madeleine Dunn <madeleine.dunn@arm.com>
Change-Id: I76b0e0bfe81be5e57d518cd7bb588eef76a11641
---
 src/mlia/nn/rewrite/core/rewrite.py | 55 ++++++++++++++++++++++++++++++-------
 1 file changed, 45 insertions(+), 10 deletions(-)

(limited to 'src/mlia/nn/rewrite/core/rewrite.py')

diff --git a/src/mlia/nn/rewrite/core/rewrite.py b/src/mlia/nn/rewrite/core/rewrite.py
index a4d47c4..2a7b432 100644
--- a/src/mlia/nn/rewrite/core/rewrite.py
+++ b/src/mlia/nn/rewrite/core/rewrite.py
@@ -12,6 +12,7 @@ from typing import Any
 from typing import Callable
 from typing import cast
 
+import tensorflow_model_optimization as tfmot
 from keras.api._v2 import keras  # Temporary workaround for now: MLIA-1107
 
 from mlia.core.errors import ConfigurationError
@@ -22,6 +23,10 @@ from mlia.nn.common import Optimizer
 from mlia.nn.common import OptimizerConfiguration
 from mlia.nn.rewrite.core.train import train
 from mlia.nn.rewrite.core.train import TrainingParameters
+from mlia.nn.rewrite.library.fc_layer import get_keras_model as fc_rewrite
+from mlia.nn.rewrite.library.fc_sparsity24_layer import (
+    get_keras_model as fc_rewrite_sparsity24,
+)
 from mlia.nn.tensorflow.config import TFLiteModel
 from mlia.utils.registry import Registry
 
@@ -45,6 +50,43 @@ class Rewrite:
         except Exception as ex:
             raise RuntimeError(f"Rewrite '{self.name}' failed.") from ex
 
+    def quantize(self, model: keras.Model, model_is_quantized: bool) -> keras.Model:
+        """Return a quantized model if required."""
+        if model_is_quantized:
+            model = tfmot.quantization.keras.quantize_model(model)
+        return model
+
+    def training_callbacks(self) -> list:
+        """Return default rewrite callbacks."""
+        return []
+
+    def post_process(self, model: keras.Model) -> keras.Model:
+        """Return default post-processing rewrite options."""
+        return model
+
+
+class PruningRewrite(Rewrite):
+    """Derived Rewrite class with pruning-specific logic."""
+
+    pruning_callback = tfmot.sparsity.keras.UpdatePruningStep
+
+    strip_pruning_wrapper = staticmethod(tfmot.sparsity.keras.strip_pruning)
+
+    def quantize(self, model: keras.Model, model_is_quantized: bool) -> keras.Model:
+        """Return a quantized model if required."""
+        if model_is_quantized:
+            # placeholder for PQAT
+            pass
+        return model
+
+    def training_callbacks(self) -> list:
+        """Return pruning-specific rewrite callback."""
+        return [self.pruning_callback()]
+
+    def post_process(self, model: keras.Model) -> keras.Model:
+        """Pruning-specific post-processing rewrite options."""
+        return self.strip_pruning_wrapper(model)
+
 
 @dataclass
 class DynamicallyLoadedRewrite(Rewrite):
@@ -113,14 +155,8 @@ class RewritingOptimizer(Optimizer):
 
     registry = RewriteRegistry(
         [
-            DynamicallyLoadedRewrite(
-                "fully-connected",
-                "mlia.nn.rewrite.library.fc_layer.get_keras_model",
-            ),
-            DynamicallyLoadedRewrite(
-                "fully-connected-sparsity24",
-                "mlia.nn.rewrite.library.fc_sparsity24_layer.get_keras_model24",
-            ),
+            Rewrite("fully-connected", fc_rewrite),
+            PruningRewrite("fully-connected-sparsity24", fc_rewrite_sparsity24),
         ]
     )
 
@@ -142,7 +178,6 @@ class RewritingOptimizer(Optimizer):
         rewrite = RewritingOptimizer.registry.items[
             self.optimizer_configuration.optimization_target
         ]
-
         use_unmodified_model = True
         tflite_model = self.model.model_path
         tfrecord = str(self.optimizer_configuration.dataset)
@@ -161,7 +196,7 @@ class RewritingOptimizer(Optimizer):
             unmodified_model=tflite_model if use_unmodified_model else None,
             output_model=str(tmp_output),
             input_tfrec=str(tfrecord),
-            replace_fn=rewrite,
+            rewrite=rewrite,
             input_tensors=[self.optimizer_configuration.layers_to_optimize[0]],
             output_tensors=[self.optimizer_configuration.layers_to_optimize[1]],
             train_params=self.optimizer_configuration.train_params,
-- 
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