feat(qat_pattern): add qat deconv pattern

mgeconvert/backend/ir_to_tflite/tflite_op.py

@@ -426,9 +426,18 @@ def _deconv(mge_opr, builder):
 
 @_register_op(ConcatOpr)
 def _concat(mge_opr, builder):
-    if len(set([t.scale for t in mge_opr.inp_tensors + mge_opr.out_tensors])) != 1:
+    if (
+        mge_opr.inp_tensors[0].q_dtype == "int8"
+        and len({t.scale for t in mge_opr.inp_tensors + mge_opr.out_tensors}) != 1
+    ):
+        logger.warning(
+            "tflite int8 concat doesn't support inputs outputs with different scale!"
+        )
+    if mge_opr.inp_tensors[0].q_dtype == "int16" and not all(
+        [t.zero_point == 0 for t in mge_opr.inp_tensors + mge_opr.out_tensors]
+    ):
         logger.warning(
-            "tflite concat doesn't support inputs outputs with different scale!"
+            "tflite int16 concat doesn't support inputs outputs with zero point != 0!"
         )
 
     ConcatenationOptions.ConcatenationOptionsStart(builder)

mgeconvert/frontend/tm_to_ir/qat_pattern.py

@@ -118,6 +118,13 @@ def gen_qat_conv_opr(module, conv_function_expr, qat_expr, irgraph, is_deconv=Fa
     MatchAnyNode,
 )
 
+pat_deconv = (
+    QATModule._apply_fakequant_with_observer,
+    MatchAnyNode,
+    (F.nn.conv_transpose2d, InputNode, QATModule._apply_fakequant_with_observer),
+    MatchAnyNode,
+)
+
 pat_deconv_relu = (
     QATModule._apply_fakequant_with_observer,
     MatchAnyNode,
@@ -168,6 +175,13 @@ def qat_conv(module, expr, call_expr, net, _):
     return op
 
 
+@register_fusion_pattern(pat_deconv)
+def qat_deconv(module, expr, call_expr, net, _):
+    conv = expr.inputs[1].expr
+    op = gen_qat_conv_opr(module, conv, call_expr, net, is_deconv=True)
+    return op
+
+
 @register_fusion_pattern(pat_deconv_bias)
 def qat_deconv_bias(module, expr, call_expr, irgraph, _):
     conv = expr.inputs[1].expr
@@ -206,6 +220,7 @@ def qat_deconv_relu_bias(
     pat_deconv_relu,
     pat_conv_relu,
     pat_conv,
+    pat_deconv,
     pat_deconv_bias,
 ]