restored QuantConvTranspose3d to tests

Xilinx · Jan 31, 2024 · ee01b84 · ee01b84
1 parent 22fe5c2
commit ee01b84
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Showing 6 changed files with 12 additions and 9 deletions.
diff --git a/tests/brevitas/export/quant_module_fixture.py b/tests/brevitas/export/quant_module_fixture.py
@@ -60,7 +60,8 @@
     QuantConv2d,
     QuantConv3d,
     QuantConvTranspose1d,
-    QuantConvTranspose2d,  #QuantConvTranspose3d,
+    QuantConvTranspose2d,
+    QuantConvTranspose3d,
 ]
 BIT_WIDTHS = [4, 8, 10]  # below 8, equal 8, above 8
 BIAS_BIT_WIDTHS = [8, 16, 32]

diff --git a/tests/brevitas/nn/nn_quantizers_fixture.py b/tests/brevitas/nn/nn_quantizers_fixture.py
@@ -95,7 +95,8 @@
     QuantConv2d,
     QuantConv3d,
     QuantConvTranspose1d,
-    QuantConvTranspose2d,  #QuantConvTranspose3d,
+    QuantConvTranspose2d,
+    QuantConvTranspose3d,
 ]
 
 ACC_BIT_WIDTHS = [8, 9, 10, 12, 16, 24, 32]

diff --git a/tests/brevitas/nn/test_a2q.py b/tests/brevitas/nn/test_a2q.py
@@ -111,9 +111,9 @@ def test_quant_wbiol_a2q(model_input, current_cases):
     elif kwargs[
             'model_type'] == 'QuantConvTranspose2d':  # shape = (in_channels, out_channels, kernel_size)
         quant_weight_per_channel_l1_norm = quant_weight.norm(p=1, dim=(0, 2, 3))
-    #elif kwargs[
-    #        'model_type'] == 'QuantConvTranspose3d':  # shape = (in_channels, out_channels, kernel_size)
-    #    quant_weight_per_channel_l1_norm = quant_weight.norm(p=1, dim=(0, 2, 3, 4))
+    elif kwargs[
+            'model_type'] == 'QuantConvTranspose3d':  # shape = (in_channels, out_channels, kernel_size)
+        quant_weight_per_channel_l1_norm = quant_weight.norm(p=1, dim=(0, 2, 3, 4))
     else:
         raise NotImplementedError(f"Check for {kwargs['model_type']} is not yet implemented.")
 

diff --git a/tests/brevitas/nn/test_wbiol.py b/tests/brevitas/nn/test_wbiol.py
@@ -32,7 +32,8 @@
     QuantConv2d,
     QuantConv3d,
     QuantConvTranspose1d,
-    QuantConvTranspose2d,  #QuantConvTranspose3d,
+    QuantConvTranspose2d,
+    QuantConvTranspose3d,
 ]
 
 

diff --git a/tests/brevitas_ort/common.py b/tests/brevitas_ort/common.py
@@ -76,7 +76,8 @@ class A2QWeightQuantizerForTests(Int8AccumulatorAwareWeightQuant):
     QuantConv2d,
     QuantConv3d,
     QuantConvTranspose1d,
-    QuantConvTranspose2d,  #QuantConvTranspose3d,
+    QuantConvTranspose2d,
+    QuantConvTranspose3d,
 ]
 
 

diff --git a/tests/brevitas_ort/test_quant_module.py b/tests/brevitas_ort/test_quant_module.py
@@ -30,8 +30,7 @@ def test_ort_wbiol(model, export_type, current_cases):
     o_bit_width = case_id.split('-')[-5]
     i_bit_width = case_id.split('-')[-3]
 
-    #if impl in ('QuantConvTranspose1d', 'QuantConvTranspose2d','QuantConvTranspose3d') and export_type == 'qop':
-    if impl in ('QuantConvTranspose1d', 'QuantConvTranspose2d') and export_type == 'qop':
+    if impl in ('QuantConvTranspose1d', 'QuantConvTranspose2d', 'QuantConvTranspose3d') and export_type == 'qop':
         pytest.skip('Export of ConvTranspose is not supported for QOperation')
     if 'per_channel' in quantizer and 'asymmetric' in quantizer:
         pytest.skip('Per-channel zero-point is not well supported in ORT.')