[GitHub] [tvm] lhutton1 commented on a change in pull request #9627: [microNPU] Add support for SIGMOID

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

lhutton1 commented on a change in pull request #9627:
URL: https://github.com/apache/tvm/pull/9627#discussion_r761119882



##########
File path: tests/python/contrib/test_ethosu/test_codegen.py
##########
@@ -1038,5 +1038,70 @@ def representative_dataset():
     infra.verify_source(compiled_models, accel_type)
 
 
+@pytest.mark.parametrize("accel_type", ACCEL_TYPES)
+@pytest.mark.parametrize("ifm_shape", [[1, 115, 32, 7], [1, 4, 5, 2]])
+def test_tflite_sigmoid(accel_type, ifm_shape):
+    dtype = "int8"
+
+    def create_tflite_graph():
+        tf.config.run_functions_eagerly(True)
+
+        class Model(tf.Module):
+            @tf.function
+            def tanh_function(self, x):

Review comment:
       ```suggestion
               def sigmoid_function(self, x):
   ```

##########
File path: python/tvm/relay/op/contrib/ethosu.py
##########
@@ -944,6 +944,35 @@ def tanh_pattern():
     return quant
 
 
+class SigmoidParams:
+    """
+    This class will parse a call to a ethos-u.sigmoid composite function
+    and extract the parameter information.
+    """
+
+    composite_name = "ethos-u.sigmoid"
+
+    def __init__(self, func_body: Call):
+        self.ofm = TensorParams(func_body)
+        self.ifm = TensorParams(func_body.args[0].args[0].args[0])
+
+    def is_valid(self):
+        """
+        This function checks whether reshape has compatible attributes with the NPU

Review comment:
       ```suggestion
           This function checks whether sigmoid has compatible attributes with the NPU
   ```

##########
File path: python/tvm/relay/backend/contrib/ethosu/legalize.py
##########
@@ -194,6 +194,76 @@ def __call__(self, *args, **kwargs):
         pass
 
 
+def sigmoid_calc_func(x):
+    """Function to calculate the values for sigmoid"""
+    # Thse limits are inherited from TFLite
+    upper_limit = 8.0
+    lower_limit = -8.0
+
+    if x <= lower_limit:
+        y = 0.0
+    elif x >= upper_limit:
+        y = 1.0
+    else:
+        y = 1 / (1 + math.exp(-x))
+    return y
+
+
+class SigmoidRewriter(DFPatternCallback):

Review comment:
       This looks very similar to `TanhRewriter`, is it worth creating a subclass?




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