darinkishore / dspy

Stanford DSPy: The framework for programming with foundation models
MIT License
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Sweep: Asynchronous Compiled Programs #7

Open darinkishore opened 8 months ago

darinkishore commented 8 months ago

Details

Currently the compiled programs are not async and hence are not efficient to serve using a python server. It would be useful to merge the PRs aiming to add async across the dspy library.

This could also involve adding nurseries in order to await an ensemble of requests simultaneously.

Checklist - [X] Modify `dspy/teleprompt/random_search.py` ✓ https://github.com/darinkishore/dspy/commit/930f948164b645f835119d20dd31d87957544c59 [Edit](https://github.com/darinkishore/dspy/edit/sweep/asynchronous_compiled_programs/dspy/teleprompt/random_search.py#L30-L146) - [X] Running GitHub Actions for `dspy/teleprompt/random_search.py` ✓ [Edit](https://github.com/darinkishore/dspy/edit/sweep/asynchronous_compiled_programs/dspy/teleprompt/random_search.py#L30-L146) - [X] Modify `dspy/teleprompt/ensemble.py` ✓ https://github.com/darinkishore/dspy/commit/09314f6b96c42d4e7bb468927b797681a3376f0e [Edit](https://github.com/darinkishore/dspy/edit/sweep/asynchronous_compiled_programs/dspy/teleprompt/ensemble.py#L11-L39) - [X] Running GitHub Actions for `dspy/teleprompt/ensemble.py` ✓ [Edit](https://github.com/darinkishore/dspy/edit/sweep/asynchronous_compiled_programs/dspy/teleprompt/ensemble.py#L11-L39) - [X] Modify `dspy/teleprompt/finetune.py` ✓ https://github.com/darinkishore/dspy/commit/215893de9abe55fa6b5a441e81869be6ebdde238 [Edit](https://github.com/darinkishore/dspy/edit/sweep/asynchronous_compiled_programs/dspy/teleprompt/finetune.py#L233-L269) - [X] Running GitHub Actions for `dspy/teleprompt/finetune.py` ✓ [Edit](https://github.com/darinkishore/dspy/edit/sweep/asynchronous_compiled_programs/dspy/teleprompt/finetune.py#L233-L269) - [X] Modify `dspy/primitives/box.py` ✓ https://github.com/darinkishore/dspy/commit/1068536d62eb0a2fd4d4789e8b60a6151e436d71 [Edit](https://github.com/darinkishore/dspy/edit/sweep/asynchronous_compiled_programs/dspy/primitives/box.py#L91-L154) - [X] Running GitHub Actions for `dspy/primitives/box.py` ✓ [Edit](https://github.com/darinkishore/dspy/edit/sweep/asynchronous_compiled_programs/dspy/primitives/box.py#L91-L154) - [X] Modify `docs/teleprompters.md` ✓ https://github.com/darinkishore/dspy/commit/0fcdd68ee4d6123d2f3a39c0edd68cd53868b212 [Edit](https://github.com/darinkishore/dspy/edit/sweep/asynchronous_compiled_programs/docs/teleprompters.md) - [X] Running GitHub Actions for `docs/teleprompters.md` ✓ [Edit](https://github.com/darinkishore/dspy/edit/sweep/asynchronous_compiled_programs/docs/teleprompters.md)
sweep-ai[bot] commented 8 months ago

🚀 Here's the PR! #16

See Sweep's progress at the progress dashboard!
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Sandbox Execution ✓

Here are the sandbox execution logs prior to making any changes:

Sandbox logs for d40f4f8
Checking dspy/teleprompt/random_search.py for syntax errors... ✅ dspy/teleprompt/random_search.py has no syntax errors! 1/1 ✓
Checking dspy/teleprompt/random_search.py for syntax errors...
✅ dspy/teleprompt/random_search.py has no syntax errors!

Sandbox passed on the latest main, so sandbox checks will be enabled for this issue.


Step 1: 🔎 Searching

I found the following snippets in your repository. I will now analyze these snippets and come up with a plan.

Some code snippets I think are relevant in decreasing order of relevance (click to expand). If some file is missing from here, you can mention the path in the ticket description. https://github.com/darinkishore/dspy/blob/6a14181ef651cc6b6282e902e2d45bbfe52545cf/dspy/primitives/box.py#L1-L155 https://github.com/darinkishore/dspy/blob/6a14181ef651cc6b6282e902e2d45bbfe52545cf/dspy/teleprompt/random_search.py#L28-L146 https://github.com/darinkishore/dspy/blob/6a14181ef651cc6b6282e902e2d45bbfe52545cf/dspy/teleprompt/ensemble.py#L6-L39 https://github.com/darinkishore/dspy/blob/6a14181ef651cc6b6282e902e2d45bbfe52545cf/docs/teleprompters.md#L1-L281

Step 2: ⌨️ Coding

--- 
+++ 
@@ -48,7 +48,7 @@
         # print("Going to sample", self.max_num_traces, "traces in total.")
         print("Will attempt to train", self.num_candidate_sets, "candidate sets.")

-    def compile(self, student, *, teacher=None, trainset, valset=None, restrict=None):
+    async def compile(self, student, *, teacher=None, trainset, valset=None, restrict=None):
         self.trainset = trainset
         self.valset = valset or trainset  # TODO: FIXME: Note this choice.

@@ -70,14 +70,14 @@
             elif seed == -2:
                 # labels only
                 teleprompter = LabeledFewShot(k=self.max_labeled_demos)
-                program2 = teleprompter.compile(student, trainset=trainset2)
+                program2 = await teleprompter.compile(student, trainset=trainset2)

             elif seed == -1:
                 # unshuffled few-shot
                 program = BootstrapFewShot(metric=self.metric, max_bootstrapped_demos=self.max_num_samples,
                                            max_labeled_demos=self.max_labeled_demos,
                                            teacher_settings=self.teacher_settings, max_rounds=self.max_rounds)
-                program2 = program.compile(student, teacher=teacher, trainset=trainset2)
+                program2 = await program.compile(student, teacher=teacher, trainset=trainset2)

             else:
                 assert seed >= 0, seed
@@ -95,7 +95,7 @@
             evaluate = Evaluate(devset=self.valset, metric=self.metric, num_threads=self.num_threads,
                                 display_table=False, display_progress=True)

-            score, subscores = evaluate(program2, return_all_scores=True)
+            score, subscores = await evaluate(program2, return_all_scores=True)

             all_subscores.append(subscores)

Ran GitHub Actions for 930f948164b645f835119d20dd31d87957544c59:

--- 
+++ 
@@ -18,11 +18,12 @@
         self.size = size
         self.deterministic = deterministic

-    def compile(self, programs):
+    async def compile(self, programs):
         size = self.size
         reduce_fn = self.reduce_fn

         import dspy
+        import asyncio
         class EnsembledProgram(dspy.Module):
             def __init__(self):
                 super().__init__()
@@ -30,7 +31,10 @@

             def forward(self, *args, **kwargs):
                 programs = random.sample(self.programs, size) if size else self.programs
-                outputs = [prog(*args, **kwargs) for prog in programs]
+                async def gather_outputs():
+                    return [await prog(*args, **kwargs) for prog in programs]
+
+                outputs = asyncio.run(gather_outputs())

                 if reduce_fn:
                     return reduce_fn(outputs)

Ran GitHub Actions for 09314f6b96c42d4e7bb468927b797681a3376f0e:

--- 
+++ 
@@ -58,7 +58,7 @@
                                              teacher_settings=teacher_settings)

-    def compile(self, student, *, teacher=None, trainset, valset=None,
+    async def compile(self, student, *, teacher=None, trainset, valset=None,
                 target='t5-large', bsize=12, accumsteps=1, lr=5e-5, epochs=1, bf16=False, int8=False, peft=False, path_prefix=None):

         # It's usually better to supply a few-shot teacher, rather than uncompiled module (the student).
@@ -72,7 +72,7 @@

         for teacher in teachers:
             # Dummy compilation to get bootstraps.
-            compiled = self.teleprompter.compile(student, teacher=teacher, trainset=trainset)
+            compiled = await self.teleprompter.compile(student, teacher=teacher, trainset=trainset)
             multitask = self.multitask

             # Prepare finetune  pairs.
@@ -141,7 +141,7 @@
             training_data_path = finetune_paths[name]
             compiler_config_ = dict(compiler_config)
             compiler_config_['save'] = compiler_config['save'] + '.' + name
-            best_ckpt_path = finetune_hf(training_data_path, target, compiler_config_)
+            best_ckpt_path = await finetune_hf(training_data_path, target, compiler_config_)

             print(f"#> Best checkpoint path: {best_ckpt_path} for {name}")
             finetune_models[name] = dsp.HFModel(model=target, checkpoint=best_ckpt_path) # best_ckpt_path

Ran GitHub Actions for 215893de9abe55fa6b5a441e81869be6ebdde238:

--- 
+++ 
@@ -99,7 +99,7 @@
         'radd', 'rsub', 'rmul', 'rtruediv', 'rfloordiv', 'rmod', 
         'rpow', 'rlshift', 'rrshift', 'rand', 'ror', 'rxor',
         # Sequence operations
-        'getitem', 'setitem', 'delitem', 'contains',
+        # 'getitem', 'setitem', 'delitem', 'contains', # Handled separately to enable async operations
         # Unary and other operations
         'neg', 'pos', 'abs', 'invert', 'round', 'len', 
         'getitem', 'setitem', 'delitem', 'contains', 'iter',
@@ -111,13 +111,14 @@

     def __init__(cls, name, bases, attrs):
         def create_method(op):
-            def method(self, other=None):
+            async def method(self, other=None):
                 if op in ['len', 'keys', 'values', 'items']:
-                    return getattr(self._value, op)()
+                    return await getattr(self._value, op)()
+                # 'getitem' and 'setitem' are special cases and must be handled outside of this loop
                 elif isinstance(other, Box):
-                    return Box(getattr(self._value, f'__{op}__')(other._value))
+                    return Box(await getattr(self._value, f'__{op}__')(other._value))
                 elif other is not None:
-                    return Box(getattr(self._value, f'__{op}__')(other))
+                    return Box(await getattr(self._value, f'__{op}__')(other))
                 else:
                     return NotImplemented
             return method
@@ -126,6 +127,13 @@
             setattr(cls, f'__{op}__', create_method(op))

         super().__init__(name, bases, attrs)
+
+    async def __getitem__(self, index):
+        return await self._value.__getitem__(index)
+
+    async def __setitem__(self, index, value):
+        await self._value.__setitem__(index, value)
+

 class Box(metaclass=BoxType):
     def __init__(self, value, source=False):
@@ -142,8 +150,8 @@
         return bool(self._value)

     # if method is missing just call it on the _value
-    def __getattr__(self, name):
-        return Box(getattr(self._value, name))
+    async def __getattr__(self, name):
+        return Box(await getattr(self._value, name))

     # # Unlike the others, this one collapses to a bool directly
     # def __eq__(self, other):

Ran GitHub Actions for 1068536d62eb0a2fd4d4789e8b60a6151e436d71:

--- 
+++ 
@@ -31,9 +31,9 @@

 ### Method

-#### `compile(self, student, *, trainset)`
-
-This method compiles the `LabeledFewShot` instance by configuring the `student` predictor. It assigns subsets of the `trainset` in each student's predictor's `demos` attribute. If the `trainset` is empty, the method returns the original `student`.
+#### `async compile(self, student, *, trainset)`
+
+This method asynchronously compiles the `LabeledFewShot` instance by configuring the `student` predictor. It assigns subsets of the `trainset` in each student's predictor's `demos` attribute. If the `trainset` is empty, the method returns the original `student`.

 **Parameters:**
 - `student` (_Teleprompter_): Student predictor to be compiled.
@@ -46,6 +46,7 @@

 ```python
 import dspy
+import asyncio

 #Assume defined trainset
 class RAG(dspy.Module):
@@ -64,6 +65,10 @@

 #Define teleprompter
 teleprompter = LabeledFewShot()
+
+# Compile!
+compiled_rag = asyncio.run(teleprompter.compile(student=RAG(), trainset=trainset))
+```

 # Compile!
 compiled_rag = teleprompter.compile(student=RAG(), trainset=trainset)

Ran GitHub Actions for 0fcdd68ee4d6123d2f3a39c0edd68cd53868b212:


Step 3: 🔁 Code Review

I have finished reviewing the code for completeness. I did not find errors for sweep/asynchronous_compiled_programs.


🎉 Latest improvements to Sweep:


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