Create configuration_flow_match.py

configuration_flow_match.py

@@ -0,0 +1,47 @@
+"""
+Configuration for FlowMatchRelay — HuggingFace compatible.
+
+Usage:
+    from transformers import AutoConfig
+    config = AutoConfig.from_pretrained("AbstractPhil/geolip-diffusion-proto", trust_remote_code=True)
+"""
+
+from transformers import PretrainedConfig
+
+
+class FlowMatchRelayConfig(PretrainedConfig):
+    model_type = "flow_match_relay"
+
+    def __init__(
+        self,
+        in_channels=3,
+        base_channels=64,
+        channel_mults=(1, 2, 4),
+        n_classes=10,
+        cond_dim=256,
+        use_relay=True,
+        relay_patch_dim=16,
+        relay_n_anchors=16,
+        relay_n_phases=3,
+        relay_pw_hidden=32,
+        relay_gate_init=-3.0,
+        relay_mode="channel",
+        image_size=32,
+        n_sample_steps=50,
+        **kwargs,
+    ):
+        self.in_channels = in_channels
+        self.base_channels = base_channels
+        self.channel_mults = list(channel_mults)
+        self.n_classes = n_classes
+        self.cond_dim = cond_dim
+        self.use_relay = use_relay
+        self.relay_patch_dim = relay_patch_dim
+        self.relay_n_anchors = relay_n_anchors
+        self.relay_n_phases = relay_n_phases
+        self.relay_pw_hidden = relay_pw_hidden
+        self.relay_gate_init = relay_gate_init
+        self.relay_mode = relay_mode
+        self.image_size = image_size
+        self.n_sample_steps = n_sample_steps
+        super().__init__(**kwargs)