#9889: Remove oldversions of sliding window code and pybind cpp funct…

…ions instead

models/experimental/functional_unet/tt/unet_shallow_ttnn.py

@@ -8,8 +8,6 @@
 
 from typing import List
 
-from ttnn.operations.conv2d import determine_parallel_config, create_sharded_memory_config_from_parallel_config
-
 from models.utility_functions import nearest_32
 from ttnn.model_preprocessing import fold_batch_norm2d_into_conv2d, ParameterDict
 
@@ -261,23 +259,26 @@ def __init__(
 
         self.should_reshard = should_reshard
         if self.should_reshard:
-            parallel_config = determine_parallel_config(
-                is_1d_systolic=True,
+            parallel_config = ttnn._ttnn.operations.conv2d.determine_parallel_config(
+                shard_layout=ttnn.TensorMemoryLayout.HEIGHT_SHARDED,
                 batch_size=self.conv1.batch_size,
                 input_channels=self.conv1.in_channels,
                 output_height=self.conv2.input_height,
                 output_width=self.conv2.input_width,
                 output_channels=self.conv1.out_channels,
                 device=device,
+                block_shard_orientation=ttnn.ShardOrientation.ROW_MAJOR,
                 is_out_tiled=True,
             )
-            self.sharded_memory_config = create_sharded_memory_config_from_parallel_config(
-                tensor_shape=[
-                    1,
-                    1,
-                    self.conv1.input_width * self.conv1.input_height * self.conv1.batch_size,
-                    nearest_32(self.conv1.in_channels),
-                ],
+            self.sharded_memory_config = ttnn._ttnn.operations.conv2d.create_sharded_memory_config_from_parallel_config(
+                tensor_shape=ttnn.Shape(
+                    [
+                        1,
+                        1,
+                        self.conv1.input_width * self.conv1.input_height * self.conv1.batch_size,
+                        nearest_32(self.conv1.in_channels),
+                    ]
+                ),
                 parallel_config=parallel_config,
                 tile_size=32 if conv1.dtype == ttnn.bfloat8_b else 1,
             )
@@ -312,23 +313,26 @@ def __init__(
 
         self.should_reshard = should_reshard
         if self.should_reshard:
-            parallel_config = determine_parallel_config(
-                is_1d_systolic=True,
+            parallel_config = ttnn._ttnn.operations.conv2d.determine_parallel_config(
+                shard_layout=ttnn.TensorMemoryLayout.HEIGHT_SHARDED,
                 batch_size=self.conv1.batch_size,
                 input_channels=self.conv1.in_channels,
                 output_height=self.conv2.input_height,
                 output_width=self.conv2.input_width,
                 output_channels=self.conv1.out_channels,
                 device=device,
+                block_shard_orientation=ttnn.ShardOrientation.ROW_MAJOR,
                 is_out_tiled=True,
             )
-            self.sharded_memory_config = create_sharded_memory_config_from_parallel_config(
-                tensor_shape=[
-                    1,
-                    1,
-                    self.conv1.input_width * self.conv1.input_height * self.conv1.batch_size,
-                    self.conv1.in_channels,
-                ],
+            self.sharded_memory_config = ttnn._ttnn.operations.conv2d.create_sharded_memory_config_from_parallel_config(
+                tensor_shape=ttnn.Shape(
+                    [
+                        1,
+                        1,
+                        self.conv1.input_width * self.conv1.input_height * self.conv1.batch_size,
+                        self.conv1.in_channels,
+                    ]
+                ),
                 parallel_config=parallel_config,
                 tile_size=32 if conv1.dtype == ttnn.bfloat8_b else 1,
             )
@@ -437,23 +441,26 @@ def __init__(self, parameters: ParameterDict, device, mesh_mapper=None) -> None:
         self.bnc2 = UNetConv2D(
             parameters.bnc_2, parameters.bnb_2, device, cache=self.conv_cache, mesh_mapper=mesh_mapper
         )
-        bnc_parallel_config = determine_parallel_config(
-            is_1d_systolic=True,
+        bnc_parallel_config = ttnn._ttnn.operations.conv2d.determine_parallel_config(
+            shard_layout=ttnn.TensorMemoryLayout.HEIGHT_SHARDED,
             batch_size=self.bnc.batch_size,
             input_channels=self.bnc.in_channels,
             output_height=self.bnc2.input_height,
             output_width=self.bnc2.input_width,
             output_channels=self.bnc.out_channels,
             device=device,
+            block_shard_orientation=ttnn.ShardOrientation.ROW_MAJOR,
             is_out_tiled=True,
         )
-        self.bnc_sharded_memory_config = create_sharded_memory_config_from_parallel_config(
-            tensor_shape=[
-                1,
-                1,
-                self.bnc.input_width * self.bnc.input_height * self.bnc.batch_size,
-                self.bnc.in_channels,
-            ],
+        self.bnc_sharded_memory_config = ttnn._ttnn.operations.conv2d.create_sharded_memory_config_from_parallel_config(
+            tensor_shape=ttnn.Shape(
+                [
+                    1,
+                    1,
+                    self.bnc.input_width * self.bnc.input_height * self.bnc.batch_size,
+                    self.bnc.in_channels,
+                ]
+            ),
             parallel_config=bnc_parallel_config,
             tile_size=(32 if self.bnc.conv_config.dtype == ttnn.bfloat8_b else 1),
         )