Add functionality to SD pipeline and abstracted components for saving output .npys

models/turbine_models/custom_models/pipeline_base.py

@@ -84,14 +84,21 @@ class PipelineComponent:
     """
 
     def __init__(
-        self, printer, dest_type="devicearray", dest_dtype="float16", benchmark=False
+        self,
+        printer,
+        dest_type="devicearray",
+        dest_dtype="float16",
+        benchmark=False,
+        save_outputs=False,
     ):
         self.runner = None
         self.module_name = None
         self.device = None
         self.metadata = None
         self.printer = printer
         self.benchmark = benchmark
+        self.save_outputs = save_outputs
+        self.output_counter = 0
         self.dest_type = dest_type
         self.dest_dtype = dest_dtype
 
@@ -218,6 +225,16 @@ def _output_cast(self, output):
             case _:
                 return output
 
+    def save_output(self, function_name, output):
+        if isinstance(output, tuple) or isinstance(output, list):
+            for i in output:
+                self.save_output(function_name, i)
+        else:
+            np.save(
+                f"{function_name}_output_{self.output_counter}.npy", output.to_host()
+            )
+            self.output_counter += 1
+
     def _run(self, function_name, inputs: list):
         return self.module[function_name](*inputs)
 
@@ -239,6 +256,8 @@ def __call__(self, function_name, inputs: list):
             output = self._run_and_benchmark(function_name, inputs)
         else:
             output = self._run(function_name, inputs)
+        if self.save_outputs:
+            self.save_output(function_name, output)
         output = self._output_cast(output)
         return output
 
@@ -340,6 +359,7 @@ def __init__(
         hf_model_name: str | dict[str] = None,
         benchmark: bool | dict[bool] = False,
         verbose: bool = False,
+        save_outputs: bool | dict[bool] = False,
         common_export_args: dict = {},
     ):
         self.map = model_map
@@ -374,6 +394,7 @@ def __init__(
             "external_weights": external_weights,
             "hf_model_name": hf_model_name,
             "benchmark": benchmark,
+            "save_outputs": save_outputs,
         }
         for arg in map_arguments.keys():
             self.map = merge_arg_into_map(self.map, map_arguments[arg], arg)
@@ -391,7 +412,7 @@ def __init__(
                 )
         for submodel in self.map.keys():
             for key, value in map_arguments.items():
-                if key != "benchmark":
+                if key not in ["benchmark", "save_outputs"]:
                     self.map = merge_export_arg(self.map, value, key)
             for key, value in self.map[submodel].get("export_args", {}).items():
                 if key == "hf_model_name":
@@ -744,6 +765,7 @@ def load_submodel(self, submodel):
             printer=self.printer,
             dest_type=dest_type,
             benchmark=self.map[submodel].get("benchmark", False),
+            save_outputs=self.map[submodel].get("save_outputs", False),
         )
         self.map[submodel]["runner"].load(
             self.map[submodel]["driver"],

models/turbine_models/custom_models/sd_inference/sd_cmd_opts.py

@@ -151,6 +151,12 @@ def is_valid_file(arg):
     help="A comma-separated list of submodel IDs for which to report benchmarks for, or 'all' for all components.",
 )
 
+p.add_argument(
+    "--save_outputs",
+    type=str,
+    default=None,
+    help="A comma-separated list of submodel IDs for which to save output .npys for, or 'all' for all components.",
+)
 ##############################################################################
 # SDXL Modelling Options
 #    These options are used to control model defining parameters for SDXL.

models/turbine_models/custom_models/sd_inference/sd_pipeline.py

@@ -236,8 +236,9 @@ def __init__(
         batch_prompts: bool = False,
         punet_quant_paths: dict[str] = None,
         vae_weight_path: str = None,
-        vae_harness: bool = False,
+        vae_harness: bool = True,
         add_tk_kernels: bool = False,
+        save_outputs: bool | dict[bool] = False,
     ):
         common_export_args = {
             "hf_model_name": None,
@@ -286,6 +287,7 @@ def __init__(
             hf_model_name,
             benchmark,
             verbose,
+            save_outputs,
             common_export_args,
         )
         for submodel in sd_model_map:
@@ -742,6 +744,14 @@ def numpy_to_pil_image(images):
                 benchmark[i] = True
     else:
         benchmark = False
+    if args.save_outputs:
+        if args.save_outputs.lower() == "all":
+            save_outputs = True
+        else:
+            for i in args.save_outputs.split(","):
+                save_outputs[i] = True
+    else:
+        save_outputs = False
     if any(x for x in [args.vae_decomp_attn, args.unet_decomp_attn]):
         args.decomp_attn = {
             "text_encoder": args.decomp_attn,
@@ -772,6 +782,7 @@ def numpy_to_pil_image(images):
         args.use_i8_punet,
         benchmark,
         args.verbose,
+        save_outputs=save_outputs,
     )
     sd_pipe.prepare_all()
     sd_pipe.load_map()