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-rw-r--r--training/conf/network/conv_perceiver.yaml37
-rw-r--r--training/conf/network/vq_transformer.yaml65
2 files changed, 0 insertions, 102 deletions
diff --git a/training/conf/network/conv_perceiver.yaml b/training/conf/network/conv_perceiver.yaml
deleted file mode 100644
index 2e12db9..0000000
--- a/training/conf/network/conv_perceiver.yaml
+++ /dev/null
@@ -1,37 +0,0 @@
-_target_: text_recognizer.networks.ConvPerceiver
-input_dims: [1, 1, 576, 640]
-hidden_dim: &hidden_dim 128
-num_classes: &num_classes 58
-max_length: &max_length 89
-num_queries: *max_length
-queries_dim: &queries_dim 64
-pad_index: 3
-encoder:
- _target_: text_recognizer.networks.EfficientNet
- arch: b0
- stochastic_dropout_rate: 0.2
- bn_momentum: 0.99
- bn_eps: 1.0e-3
- depth: 5
- out_channels: *hidden_dim
-decoder:
- _target_: text_recognizer.networks.perceiver.PerceiverIO
- dim: 192
- cross_heads: 1
- cross_head_dim: 64
- num_latents: 256
- latent_dim: 512
- latent_heads: 8
- depth: 6
- queries_dim: 128
- logits_dim: *num_classes
-pixel_embedding:
- _target_: text_recognizer.networks.transformer.embeddings.axial.AxialPositionalEmbeddingImage
- dim: 64
- axial_shape: [3, 64]
- axial_dims: [32, 32]
-query_pos_emb:
- _target_: text_recognizer.networks.transformer.embeddings.absolute.AbsolutePositionalEmbedding
- dim: 64
- max_seq_len: *max_length
- l2norm_embed: true
diff --git a/training/conf/network/vq_transformer.yaml b/training/conf/network/vq_transformer.yaml
deleted file mode 100644
index d62a4b7..0000000
--- a/training/conf/network/vq_transformer.yaml
+++ /dev/null
@@ -1,65 +0,0 @@
-_target_: text_recognizer.networks.VqTransformer
-input_dims: [1, 1, 576, 640]
-hidden_dim: &hidden_dim 144
-num_classes: 58
-pad_index: 3
-encoder:
- _target_: text_recognizer.networks.EfficientNet
- arch: b0
- stochastic_dropout_rate: 0.2
- bn_momentum: 0.99
- bn_eps: 1.0e-3
- depth: 5
- out_channels: *hidden_dim
-decoder:
- _target_: text_recognizer.networks.transformer.Decoder
- depth: 6
- block:
- _target_: text_recognizer.networks.transformer.DecoderBlock
- self_attn:
- _target_: text_recognizer.networks.transformer.Attention
- dim: *hidden_dim
- num_heads: 8
- dim_head: 64
- dropout_rate: &dropout_rate 0.4
- causal: true
- rotary_embedding:
- _target_: text_recognizer.networks.transformer.RotaryEmbedding
- dim: 64
- cross_attn:
- _target_: text_recognizer.networks.transformer.Attention
- dim: *hidden_dim
- num_heads: 8
- dim_head: 64
- dropout_rate: *dropout_rate
- causal: false
- norm:
- _target_: text_recognizer.networks.transformer.RMSNorm
- dim: *hidden_dim
- ff:
- _target_: text_recognizer.networks.transformer.FeedForward
- dim: *hidden_dim
- dim_out: null
- expansion_factor: 2
- glu: true
- dropout_rate: *dropout_rate
-pixel_embedding:
- _target_: text_recognizer.networks.transformer.AxialPositionalEmbedding
- dim: *hidden_dim
- shape: [18, 79]
-quantizer:
- _target_: text_recognizer.networks.quantizer.VectorQuantizer
- input_dim: *hidden_dim
- codebook:
- _target_: text_recognizer.networks.quantizer.CosineSimilarityCodebook
- dim: 16
- codebook_size: 64
- kmeans_init: true
- kmeans_iters: 10
- decay: 0.8
- eps: 1.0e-5
- threshold_dead: 2
- temperature: 0.0
- commitment: 0.25
- ort_reg_weight: 10
- ort_reg_max_codes: 64