Delete base.yaml

base.yaml

@@ -1,58 +0,0 @@
-pixel_mean: [0.485, 0.456, 0.406]
-pixel_std: [0.229, 0.224, 0.225]
-
-pixel_dim: 256
-key_dim: 64
-value_dim: 256
-sensory_dim: 256
-embed_dim: 256
-
-pixel_encoder:
-  type: resnet50
-  ms_dims: [1024, 512, 256, 64, 3] # f16, f8, f4, f2, f1
-
-mask_encoder:
-  type: resnet18
-  final_dim: 256
-
-pixel_pe_scale: 32
-pixel_pe_temperature: 128
-
-object_transformer:
-  embed_dim: ${model.embed_dim}
-  ff_dim: 2048
-  num_heads: 8
-  num_blocks: 3
-  num_queries: 16
-  read_from_pixel:
-    input_norm: False
-    input_add_pe: False
-    add_pe_to_qkv: [True, True, False]
-  read_from_past:
-    add_pe_to_qkv: [True, True, False]
-  read_from_memory:
-    add_pe_to_qkv: [True, True, False]
-  read_from_query:
-    add_pe_to_qkv: [True, True, False]
-    output_norm: False
-  query_self_attention:
-    add_pe_to_qkv: [True, True, False]
-  pixel_self_attention:
-    add_pe_to_qkv: [True, True, False]
-
-object_summarizer:
-  embed_dim: ${model.object_transformer.embed_dim}
-  num_summaries: ${model.object_transformer.num_queries}
-  add_pe: True
-
-aux_loss:
-  sensory:
-    enabled: True
-    weight: 0.01
-  query:
-    enabled: True
-    weight: 0.01
-
-mask_decoder:
-  # first value must equal embed_dim
-  up_dims: [256, 128, 128, 64, 16]