Upload config

config.json

@@ -0,0 +1,77 @@
+{
+  "attentions": [
+    0,
+    0,
+    0,
+    0,
+    0,
+    0,
+    0
+  ],
+  "auto_map": {
+    "AutoConfig": "dmae_config.DMAE1dConfig"
+  },
+  "bottleneck": "tanh",
+  "channels": 512,
+  "encoder_channels": 32,
+  "encoder_factors": [
+    1,
+    1,
+    2,
+    2,
+    1,
+    1
+  ],
+  "encoder_inject_depth": 3,
+  "encoder_multipliers": [
+    32,
+    16,
+    8,
+    8,
+    4,
+    2,
+    1
+  ],
+  "encoder_num_blocks": [
+    4,
+    4,
+    4,
+    4,
+    4,
+    4
+  ],
+  "factors": [
+    1,
+    2,
+    2,
+    2,
+    2,
+    2,
+    2
+  ],
+  "in_channels": 2,
+  "model_type": "archinetai/dmae1d-ATC64-v1",
+  "multipliers": [
+    3,
+    2,
+    1,
+    1,
+    1,
+    1,
+    1,
+    1
+  ],
+  "num_blocks": [
+    1,
+    1,
+    1,
+    2,
+    2,
+    2,
+    2
+  ],
+  "stft_hop_length": 256,
+  "stft_num_fft": 1023,
+  "stft_use_complex": true,
+  "transformers_version": "4.24.0"
+}

dmae_config.py

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+from transformers import PretrainedConfig
+from typing import Sequence
+
+class DMAE1dConfig(PretrainedConfig):
+
+    model_type = "archinetai/dmae1d-ATC64-v1"
+
+    def __init__(
+        self,
+        in_channels: int = 2,  
+        channels: int = 512,              
+        multipliers: Sequence[int] = [3, 2, 1, 1, 1, 1, 1, 1],
+        factors: Sequence[int] = [1, 2, 2, 2, 2, 2, 2],
+        num_blocks: Sequence[int] = [1, 1, 1, 2, 2, 2, 2],
+        attentions: Sequence[int] = [0, 0, 0, 0, 0, 0, 0], 
+        encoder_inject_depth: int = 3,
+        encoder_channels: int = 32,
+        encoder_factors: Sequence[int] = [1, 1, 2, 2, 1, 1],
+        encoder_multipliers: Sequence[int] = [32, 16, 8, 8, 4, 2, 1],
+        encoder_num_blocks: Sequence[int] = [4, 4, 4, 4, 4, 4],
+        bottleneck: str = 'tanh',
+        stft_use_complex: bool = True, 
+        stft_num_fft: int = 1023,
+        stft_hop_length: int = 256,
+        **kwargs 
+    ):
+        self.in_channels = in_channels 
+        self.channels = channels 
+        self.multipliers = multipliers 
+        self.factors = factors 
+        self.num_blocks = num_blocks 
+        self.attentions = attentions 
+        self.encoder_inject_depth = encoder_inject_depth 
+        self.encoder_channels = encoder_channels 
+        self.encoder_factors = encoder_factors
+        self.encoder_multipliers = encoder_multipliers 
+        self.encoder_num_blocks = encoder_num_blocks
+        self.bottleneck = bottleneck 
+        self.stft_use_complex = stft_use_complex 
+        self.stft_num_fft = stft_num_fft 
+        self.stft_hop_length = stft_hop_length 
+        super().__init__(**kwargs)
+