[QNN] Add nn.adaptive_avg_pool1d to FQ2I (#10541)

* add adaptive avg pool 1d

* clean up

* lint

Co-authored-by: Margaret Qian <mqian@octoml.ai>

Author: margaretqian

python/tvm/relay/transform/fake_quantization_to_integer.py

@@ -108,6 +108,17 @@ def identity(expr, type_map):
 register_unary_identity("min")
 
 
+@register_fake_quantization_to_integer("nn.adaptive_avg_pool1d")
+def adaptive_avgpool1d(expr, type_map):
+    """Rewrite an adaptive avgpool op"""
+    arg = expr.args[0]
+    t = type_map[arg]
+    arg = relay.op.cast(arg, "int32")
+    out = relay.op.nn.adaptive_avg_pool1d(arg)
+    out = relay.op.cast(out, t.dtype)
+    return [out, t]
+
+
 @register_fake_quantization_to_integer("nn.avg_pool2d")
 def avgpool2d(expr, type_map):
     """Rewrite a avgpool op"""

tests/python/relay/test_pass_fake_quantization_to_integer.py

@@ -277,6 +277,19 @@ def test_fake_quantize_maxpool():
     compare_fq_to_int(op, [x_np])
 
 
+def test_fake_quantize_adaptive_avgpool1d():
+    x = relay.var("x", shape=[1, 3, 224, 224], dtype="int8")
+
+    zero = relay.const(0)
+    x = relay.qnn.op.dequantize(x, relay.const(2.0), zero)
+    op = relay.op.nn.adaptive_avg_pool1d(x)
+    op = relay.qnn.op.quantize(op, relay.const(2.0), zero)
+
+    x_np = np.random.randint(-128, 127, size=[1, 3, 224, 224], dtype="int8")
+
+    compare_fq_to_int(op, [x_np], True)
+
+
 def test_fake_quantize_avgpool():
     x = relay.var("x", shape=[1, 3, 224, 224], dtype="int8")