Removed print statements

models/GroundingDINO/groundingdino.py

@@ -397,7 +397,6 @@ class GroundingDINO(nn.Module):
                             dictionnaries containing the two above keys for each decoder layer.
         """
 
-        print("inside forward")
         if targets is None:
             captions = kw["captions"]
         else:
@@ -409,7 +408,6 @@ class GroundingDINO(nn.Module):
             samples.device
         )
 
-        print("tokenized text")
         one_hot_token = tokenized
 
         (
@@ -445,7 +443,6 @@ class GroundingDINO(nn.Module):
 
         bert_output = self.bert(**tokenized_for_encoder)  # bs, 195, 768
 
-        print("got bert output")
         encoded_text = self.feat_map(
             bert_output["last_hidden_state"]
         )  # bs, 195, d_model
@@ -494,7 +491,6 @@ class GroundingDINO(nn.Module):
             else:
                 exemplar_tokens = None
 
-            print("got visual exemplar tokens")
 
         else:
             features, poss = self.backbone(samples)
@@ -576,7 +572,6 @@ class GroundingDINO(nn.Module):
         srcs = []
         masks = []
         for l, feat in enumerate(features):
-            print("l: " + str(l))
             src, mask = feat.decompose()
             srcs.append(self.input_proj[l](src))
             masks.append(mask)
@@ -598,13 +593,10 @@ class GroundingDINO(nn.Module):
                 poss.append(pos_l)
 
         input_query_bbox = input_query_label = attn_mask = dn_meta = None
-        print("passing info through transformer")
         hs, reference, hs_enc, ref_enc, init_box_proposal = self.transformer(
             srcs, masks, input_query_bbox, poss, input_query_label, attn_mask, text_dict
         )
 
-        print("passed info through transformer")
-
         # deformable-detr-like anchor update
         outputs_coord_list = []
         for dec_lid, (layer_ref_sig, layer_bbox_embed, layer_hs) in enumerate(
@@ -681,7 +673,6 @@ class GroundingDINO(nn.Module):
         # outputs['one_hot'].shape
         # torch.Size([4, 900, 256])
 
-        print("returning out")
         return out
 
     @torch.jit.unused