[GitHub] [tvm] NicolaLancellotti commented on a change in pull request #9384: Arm(R) Ethos(TM)-U NPU Pooling operators support

[GitBox <gi...@apache.org>]

NicolaLancellotti commented on a change in pull request #9384:
URL: https://github.com/apache/tvm/pull/9384#discussion_r738595291



##########
File path: python/tvm/relay/backend/contrib/ethosu/te/pooling.py
##########
@@ -0,0 +1,134 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+# pylint: disable=invalid-name,unused-argument
+"""Tensor Expressions for poolings"""
+from typing import Tuple
+
+from tvm import te
+from .dma import dma_ofm_compute, dma_ifm_compute
+
+
+def pooling_compute(
+    ifm: te.Tensor,
+    lut: te.Tensor,
+    pooling_type: str,
+    ifm_scale: float,
+    ifm_zero_point: int,
+    ofm_scale: float,
+    ofm_zero_point: int,
+    pool_shape: Tuple[int, int],
+    ofm_channels: int,
+    strides: Tuple[int, int],
+    padding: Tuple[int, int, int, int],
+    activation: str,
+    clip_min: int,
+    clip_max: int,
+    upscale: str,
+    ifm_layout: str,
+    ofm_layout: str,
+) -> te.Tensor:
+    """A compute operator representing the capabilities of pooling for the NPU.
+
+    Parameters
+    ----------
+    ifm : te.Tensor
+        The Input Feature Map tensor (IFM).
+    lut : te.Tensor
+        The look-up table values to use if activation = "LUT".
+    pooling_type: str
+        The type of the pooling. "AVG" - average pool,   "MAX" - max pool.
+    ifm_scale : float
+        The quantization scale for the Input Feature Map tensor.
+    ifm_zero_point : int
+        The quantization zero point for the Input Feature Map tensor.
+    ofm_scale : float
+        The quantization scale for the Output Feature Map tensor.
+    ofm_zero_point : int
+        The quantization zero point for the Output Feature Map tensor.
+    pool_shape : Tuple[int, int]
+        The 2 dimensional pool shape as (pool_shape_height, pool_shape_width).
+    ofm_channels : int
+        The number of OFM channels
+    strides : Tuple[int, int]
+        The 2 dimensional strides as (stride_height, stride_width).
+    padding : Tuple[int, int, int, int]
+        The 4 dimensional padding as (pad_top, pad_left, pad_bottom, pad_right).
+    activation : str
+        The activation function to use.
+            "NONE" - no activation function.
+            "CLIP" - clip the output between clip_min and clip_max.
+            "TANH" - tanh activation function.
+            "SIGMOID" - sigmoid activation function.
+            "LUT" - use a look-up table to perform the activation function.
+    clip_min : int
+        The minimum clipping value if activation = "CLIP".
+    clip_max : int
+        The maximum clipping value if activation = "CLIP".
+    upscale : str
+        The 2x2 upscaling mode to apply to the Input Feature Map tensor.
+            "NONE" - no upscaling.
+            "NEAREST" - upscale using nearest neighbour.
+            "ZEROS" - upscale using zeros.
+    ifm_layout : str
+        The layout of the Input Feature Map tensor. Can be "NHWC" or "NHCWB16".
+    ofm_layout : str
+        The layout of the Output Feature Map tensor. Can be "NHWC" or "NHCWB16".
+
+    Returns
+    -------
+    te.Tensor
+        The OFM tensor.
+    """
+    assert ifm.shape[0] == 1, f"Only batch size 1 is supported"

Review comment:
       No, these asserts are not reachable.

##########
File path: python/tvm/relay/backend/contrib/ethosu/util.py
##########
@@ -75,6 +75,15 @@ class ClipArgs(Enum):
     A_MAX = 2
 
 
+class MaxPoolArgs(Enum):
+    """
+    This is a helper enums to access the correct index
+    of max pool arguments
+    """
+
+    ifm = 0
+
+

Review comment:
       I agree, I'll remove it.

##########
File path: python/tvm/relay/backend/contrib/ethosu/util.py
##########
@@ -75,6 +75,15 @@ class ClipArgs(Enum):
     A_MAX = 2
 
 
+class MaxPoolArgs(Enum):
+    """
+    This is a helper enums to access the correct index
+    of max pool arguments
+    """
+
+    ifm = 0
+
+

Review comment:
       The same as above.




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