GroqFlow release v4.2.1

groq · Sep 29, 2023 · 99b71dd · 99b71dd
1 parent 43da677
commit 99b71dd
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Showing 3 changed files with 19 additions and 2 deletions.
diff --git a/groqflow/justgroqit/compile.py b/groqflow/justgroqit/compile.py
@@ -84,10 +84,22 @@ def fire(self, state: build.GroqState):
         if state.num_chips_used != 1:
             multichip_flag = f"--multichip={state.topology}"
             cmd = cmd + [multichip_flag]
+            if not any(
+                flag.startswith("--partition-mode=")
+                for flag in state.config.compiler_flags
+            ):
+                partition_mode_flag = "--partition-mode=daisy-chain"
+                cmd = cmd + [partition_mode_flag]
 
         if state.config.groqview:
             cmd = cmd + ["--groqview"]
 
+        # Add effort=standard by default to help with fit-ability
+        if not any(
+            flag.startswith("--effort=") for flag in state.config.compiler_flags
+        ):
+            cmd = cmd + ["--effort=standard"]
+
         # Add flags
         cmd = (
             cmd

diff --git a/proof_points/natural_language_processing/distilbert/README.md b/proof_points/natural_language_processing/distilbert/README.md
@@ -29,4 +29,4 @@ To build and evaluate DistilBERT:
 
 ## Expected Results
 
-It takes approximately 8 minutes for DistilBERT to build and about 2 minutes to evaluate the model's accuracy. The example returns the accuracies for both the PyTorch implementation on a CPU and the Groq implementation on 2 GroqCard™ accelerators within a GroqNode™ server.
+It takes approximately 8 minutes for DistilBERT to build and about 2 minutes to evaluate the model's accuracy. The example returns the accuracies for both the PyTorch implementation on a CPU and the Groq implementation on 4 GroqCard™ accelerators within a GroqNode™ server.
diff --git a/proof_points/natural_language_processing/distilbert/distilbert.py b/proof_points/natural_language_processing/distilbert/distilbert.py
@@ -33,7 +33,12 @@ def evaluate_distilbert(rebuild_policy=None, should_execute=True):
     # generate groq model
     build_name = "distilbert"
     groq_model = groqit(
-        pytorch_model, dummy_inputs, rebuild=rebuild_policy, build_name=build_name
+        pytorch_model,
+        dummy_inputs,
+        rebuild=rebuild_policy,
+        build_name=build_name,
+        num_chips=4,
+        compiler_flags=["--partition-mode=group-fit"],
     )
 
     # compute performance on CPU and GroqChip
Original file line number	Diff line number	Diff line change
Expand Up		@@ -29,4 +29,4 @@ To build and evaluate DistilBERT:

		## Expected Results

		It takes approximately 8 minutes for DistilBERT to build and about 2 minutes to evaluate the model's accuracy. The example returns the accuracies for both the PyTorch implementation on a CPU and the Groq implementation on 2 GroqCard™ accelerators within a GroqNode™ server.
		It takes approximately 8 minutes for DistilBERT to build and about 2 minutes to evaluate the model's accuracy. The example returns the accuracies for both the PyTorch implementation on a CPU and the Groq implementation on 4 GroqCard™ accelerators within a GroqNode™ server.