More fixes

Author: Alejandro Gaston Alvarez Franceschi

coremltools/converters/mil/frontend/torch/test/test_torch_ops.py

@@ -9597,7 +9597,7 @@ def forward(self, x):
             [None, 4, 5], # hop_length
             [None, 16, 9], # win_length
             [None, torch.hann_window], # window
-            [None, False, True], # center
+            [False, True], # center
             [False, True], # normalized
             [None, False, True], # onesided
             [None, 60], # length

coremltools/converters/mil/mil/ops/defs/complex_dialect_ops.py

@@ -934,7 +934,9 @@ def type_inference(self):
             output_shape += [self.length]
         else:
             n_frames = self.input.shape[-1]
-            output_shape += [self.n_fft.val + self.hop_length.val * (n_frames - 1)]
+
+            hop_length = self.hop_length.val if self.hop_length else self.n_fft.val // 4
+            output_shape += [self.n_fft.val + hop_length * (n_frames - 1)]
 
 
         return types.tensor(output_type, tuple(output_shape))

coremltools/converters/mil/mil/passes/defs/lower_complex_dialect_ops.py

@@ -481,11 +481,11 @@ def _istft(
 
     # We need to adapt last dimension
     if length is not None:
-        if length > expected_output_signal_len:
+        if length.val > expected_output_signal_len:
             right_pad = mb.fill(shape=(channels, expected_output_signal_len - length), value=0., before_op=before_op)
             real_result = mb.stack(x=(real_result, right_pad), axis=1, before_op=before_op)
             imag_result = mb.stack(x=(imag_result, right_pad), axis=1, before_op=before_op)
-        elif length < expected_output_signal_len:
+        elif length.val < expected_output_signal_len:
             real_result = mb.slice_by_size(x=real_result, begin=[0], size=[length], before_op=before_op)
             imag_result = mb.slice_by_size(x=imag_result, begin=[0], size=[length], before_op=before_op)