ops: Implement prefetching API

Implement an API that allows instrumenting a model with a prefetch
queue. Units of work are on the nn.Module level.

Author: rattus128

comfy/ops.py

@@ -71,6 +71,93 @@ def cast_to_input(weight, input, non_blocking=False, copy=True):
     return comfy.model_management.cast_to(weight, input.dtype, input.device, non_blocking=non_blocking, copy=copy)
 
 
+def cast_prefetch_all(module, device):
+    if not comfy.model_management.device_supports_non_blocking(device):
+        #Adios! prefetching works against you if you can't get the CPU past it
+        return None
+
+    offload_stream = None
+
+    for n, m in module.named_modules():
+        if hasattr(m, "comfy_cast_weights"):
+            if m.weight is not None and m.weight.device != device and not hasattr(m, "weight_prefetch"):
+                if offload_stream is None:
+                    offload_stream = comfy.model_management.get_offload_stream(device)
+                    if offload_stream is None:
+                        return None
+                m.weight_prefetch = comfy.model_management.cast_to(m.weight, None, device, non_blocking=True, copy=True, stream=offload_stream)
+            if m.bias is not None and m.bias.device != device and not hasattr(m, "bias_prefetch"):
+                if offload_stream is None:
+                    offload_stream = comfy.model_management.get_offload_stream(device)
+                    if offload_stream is None:
+                        return None
+                m.bias_prefetch = comfy.model_management.cast_to(m.bias, None, device, non_blocking=True, copy = True, stream=offload_stream)
+
+    return offload_stream
+
+
+def uncast_prefetch_all(module):
+    for n, m in module.named_modules():
+        if hasattr(m, "comfy_cast_weights"):
+            if hasattr(m, "weight_prefetch"):
+                delattr(m, "weight_prefetch")
+            if hasattr(m, "bias_prefetch"):
+                delattr(m, "bias_prefetch")
+
+
+def prefetch_queue_pop(queue, device, module):
+    consumed = queue.pop(0)
+    if consumed is not None:
+        offload_stream, m = consumed
+        #Sync the offload stream with compute so when it starts
+        #freeing the prefetches the compute stream has finished
+        if offload_stream is not None:
+            offload_stream.wait_stream(comfy.model_management.current_stream(device))
+            uncast_prefetch_all(m)
+
+    active = queue[0]
+    if active is not None:
+        offload_stream, m = active
+        assert m == module
+        #wait for the prefetch to complete before using the data
+        if offload_stream is not None:
+            comfy.model_management.sync_stream(device, offload_stream)
+
+    prefetch = queue[1]
+    if prefetch is not None:
+        offload_stream = comfy.ops.cast_prefetch_all(prefetch, device)
+        queue[1] = (offload_stream, prefetch)
+
+
+def make_prefetch_queue(queue):
+    return [None, None] + queue + [None, None]
+
+
+def move_bias_weight(s, device, offloadable=False):
+
+    bias_has_function = len(s.bias_function) > 0
+    weight_has_function = len(s.weight_function) > 0
+
+    if offloadable and (
+            s.weight.device != device or (s.bias is not None and s.bias.device != device) or
+            bias_has_function or weight_has_function):
+        offload_stream = comfy.model_management.get_offload_stream(device)
+    else:
+        offload_stream = None
+
+    bias = None
+    non_blocking = comfy.model_management.device_supports_non_blocking(device)
+
+    weight = comfy.model_management.cast_to(s.weight, None, device, non_blocking=non_blocking, copy=weight_has_function, stream=offload_stream)
+
+    if s.bias is not None:
+        bias = comfy.model_management.cast_to(s.bias, None, device, non_blocking=non_blocking, copy=bias_has_function, stream=offload_stream)
+
+    comfy.model_management.sync_stream(device, offload_stream)
+
+    return weight, bias, offload_stream
+
+
 @torch.compiler.disable()
 def cast_bias_weight(s, input=None, dtype=None, device=None, bias_dtype=None, offloadable=False):
     # NOTE: offloadable=False is a a legacy and if you are a custom node author reading this please pass
@@ -84,40 +171,35 @@ def cast_bias_weight(s, input=None, dtype=None, device=None, bias_dtype=None, of
         if device is None:
             device = input.device
 
-    if offloadable and (device != s.weight.device or
-                        (s.bias is not None and device != s.bias.device)):
-        offload_stream = comfy.model_management.get_offload_stream(device)
-    else:
+    bias_has_function = len(s.bias_function) > 0
+    weight_has_function = len(s.weight_function) > 0
+
+    if hasattr(s, "weight_prefetch") or hasattr(s, "bias_prefetch"):
+        weight = getattr(s, "weight_prefetch", None)
+        bias = getattr(s, "bias_prefetch", None)
         offload_stream = None
+    else:
+        weight, bias, offload_stream = move_bias_weight(s, device, offloadable=offloadable)
 
     if offload_stream is not None:
         wf_context = offload_stream
     else:
         wf_context = contextlib.nullcontext()
 
-    non_blocking = comfy.model_management.device_supports_non_blocking(device)
-
-    weight_has_function = len(s.weight_function) > 0
-    bias_has_function = len(s.bias_function) > 0
-
-    weight = comfy.model_management.cast_to(s.weight, None, device, non_blocking=non_blocking, copy=weight_has_function, stream=offload_stream)
-
-    bias = None
-    if s.bias is not None:
-        bias = comfy.model_management.cast_to(s.bias, bias_dtype, device, non_blocking=non_blocking, copy=bias_has_function, stream=offload_stream)
+    if weight_has_function:
+        weight=weight.to(dtype=dtype)
+        for f in s.weight_function:
+            weight = f(weight)
 
-        if bias_has_function:
-            with wf_context:
-                for f in s.bias_function:
-                    bias = f(bias)
+    if s.bias is not None and bias_has_function:
+        bias=bias.to(dtype=bias_dtype)
+        for f in s.bias_function:
+            bias = f(bias)
 
-    weight = weight.to(dtype=dtype)
-    if weight_has_function:
-        with wf_context:
-            for f in s.weight_function:
-                weight = f(weight)
+    weight=weight.to(dtype=dtype)
+    if bias is not None:
+        bias=bias.to(dtype=bias_dtype)
 
-    comfy.model_management.sync_stream(device, offload_stream)
     if offloadable:
         return weight, bias, offload_stream
     else: