Use DYNAMIC on batch size (#213)

* use DYNAMIC(str)

* delete check-urls.yml

* Revert "delete check-urls.yml"

This reverts commit 6983c2c.

Author: titaiwangms

onnx_diagnostic/tasks/automatic_speech_recognition.py

@@ -76,7 +76,7 @@ def get_inputs(
     assert (
         "cls_cache" not in kwargs
     ), f"Not yet implemented for cls_cache={kwargs['cls_cache']!r}."
-    batch = torch.export.Dim("batch", min=1, max=1024)
+    batch = "batch"
     seq_length = "seq_length"
 
     shapes = {

onnx_diagnostic/tasks/feature_extraction.py

@@ -47,7 +47,7 @@ def get_inputs(
     assert (
         "cls_cache" not in kwargs
     ), f"Not yet implemented for cls_cache={kwargs['cls_cache']!r}."
-    batch = torch.export.Dim("batch", min=1, max=1024)
+    batch = "batch"
     seq_length = "sequence_length"
     shapes = {
         "input_ids": {0: batch, 1: seq_length},

onnx_diagnostic/tasks/fill_mask.py

@@ -42,7 +42,7 @@ def get_inputs(
     assert (
         "cls_cache" not in kwargs
     ), f"Not yet implemented for cls_cache={kwargs['cls_cache']!r}."
-    batch = torch.export.Dim("batch", min=1, max=1024)
+    batch = "batch"
     seq_length = "sequence_length"
     shapes = {
         "input_ids": {0: batch, 1: seq_length},

onnx_diagnostic/tasks/image_text_to_text.py

@@ -107,7 +107,7 @@ def _get_inputs_gemma3(
     assert (
         "cls_cache" not in kwargs
     ), f"Not yet implemented for cls_cache={kwargs['cls_cache']!r}."
-    batch = torch.export.Dim("batch", min=1, max=1024)
+    batch = "batch"
     seq_length = "seq_length"  # torch.export.Dim("seq_length", min=1, max=4096)
     # cache_length = "cache_length"  # torch.export.Dim("cache_length", min=1, max=4096)
 
@@ -230,7 +230,7 @@ def get_inputs(
         assert (
             "cls_cache" not in kwargs
         ), f"Not yet implemented for cls_cache={kwargs['cls_cache']!r}."
-        batch = torch.export.Dim("batch", min=1, max=1024)
+        batch = "batch"
         batch_img = torch.export.Dim("batch_img", min=1, max=1024)
         seq_length = "seq_length"  # torch.export.Dim("seq_length", min=1, max=4096)
         cache_length = "cache_length"  # torch.export.Dim("cache_length", min=1, max=4096)

onnx_diagnostic/tasks/sentence_similarity.py

@@ -42,7 +42,7 @@ def get_inputs(
     assert (
         "cls_cache" not in kwargs
     ), f"Not yet implemented for cls_cache={kwargs['cls_cache']!r}."
-    batch = torch.export.Dim("batch", min=1, max=1024)
+    batch = "batch"
     seq_length = "seq_length"
     shapes = {
         "input_ids": {0: batch, 1: seq_length},

onnx_diagnostic/tasks/summarization.py

@@ -70,7 +70,7 @@ def get_inputs(
     assert (
         "cls_cache" not in kwargs
     ), f"Not yet implemented for cls_cache={kwargs['cls_cache']!r}."
-    batch = torch.export.Dim("batch", min=1, max=1024)
+    batch = "batch"
     seq_length = "seq_length"  # torch.export.Dim("seq_length", min=1, max=4096)
     cache_length = "cache_length_key"  # torch.export.Dim("cache_length", min=1, max=4096)
     cache_length2 = "cache_length_val"  # torch.export.Dim("cache_length2", min=1, max=4096)

onnx_diagnostic/tasks/text2text_generation.py

@@ -72,7 +72,7 @@ def get_inputs(
     assert (
         "cls_cache" not in kwargs
     ), f"Not yet implemented for cls_cache={kwargs['cls_cache']!r}."
-    batch = torch.export.Dim("batch", min=1, max=1024)
+    batch = "batch"
     seq_length = "seq_length"  # torch.export.Dim("seq_length", min=1, max=4096)
     cache_length = "cache_length_key"
     cache_length2 = "cache_length_val"

onnx_diagnostic/tasks/text_classification.py

@@ -42,7 +42,7 @@ def get_inputs(
     assert (
         "cls_cache" not in kwargs
     ), f"Not yet implemented for cls_cache={kwargs['cls_cache']!r}."
-    batch = torch.export.Dim("batch", min=1, max=1024)
+    batch = "batch"
     seq_length = "seq_length"  # torch.export.Dim("sequence_length", min=1, max=1024)
     shapes = {
         "input_ids": {0: batch, 1: seq_length},

onnx_diagnostic/tasks/text_generation.py

@@ -83,7 +83,7 @@ def get_inputs(
         :class:`transformers.cache_utils.DynamicCache`
     :return: dictionary
     """
-    batch = torch.export.Dim("batch", min=1, max=1024)
+    batch = "batch"
     seq_length = "seq_length"  # torch.export.Dim("seq_length", min=1, max=4096)
     cache_length = "cache_length"  # torch.export.Dim("cache_length", min=1, max=4096)
 

onnx_diagnostic/tasks/zero_shot_image_classification.py

@@ -65,7 +65,7 @@ def get_inputs(
         input_width, int
     ), f"Unexpected type for input_height {type(input_height)}{config}"
 
-    batch = torch.export.Dim("batch", min=1, max=1024)
+    batch = "batch"
     seq_length = "seq_length"  # torch.export.Dim("seq_length", min=1, max=4096)
     shapes = {
         "input_ids": {0: batch, 1: seq_length},