From 38d6543502af2475e0b840fad0a8d5e87a6f550a Mon Sep 17 00:00:00 2001
From: Yaman Umuroglu <maltanar@gmail.com>
Date: Tue, 13 Sep 2022 23:35:18 +0200
Subject: [PATCH] [Build] support batched verification i/o, one at a time
---
src/finn/builder/build_dataflow_steps.py | 110 +++++++++++++++--------
1 file changed, 73 insertions(+), 37 deletions(-)
diff --git a/src/finn/builder/build_dataflow_steps.py b/src/finn/builder/build_dataflow_steps.py
index 59f77650d..0aae7c9e6 100644
--- a/src/finn/builder/build_dataflow_steps.py
+++ b/src/finn/builder/build_dataflow_steps.py
@@ -121,44 +121,80 @@ def verify_step(
verify_out_dir = cfg.output_dir + "/verification_output"
intermediate_models_dir = cfg.output_dir + "/intermediate_models"
os.makedirs(verify_out_dir, exist_ok=True)
- (in_npy, exp_out_npy) = cfg._resolve_verification_io_pair()
- if need_parent:
- assert (
- cfg.save_intermediate_models
- ), "Enable save_intermediate_models for verification"
- parent_model_fn = intermediate_models_dir + "/dataflow_parent.onnx"
- child_model_fn = intermediate_models_dir + "/verify_%s.onnx" % step_name
- model.save(child_model_fn)
- out_tensor_name = ModelWrapper(parent_model_fn).graph.output[0].name
- out_dict = execute_parent(
- parent_model_fn, child_model_fn, in_npy, return_full_ctx=True
- )
- out_npy = out_dict[out_tensor_name]
- else:
- inp_tensor_name = model.graph.input[0].name
- out_tensor_name = model.graph.output[0].name
- inp_dict = {inp_tensor_name: in_npy}
- if rtlsim_pre_hook is not None:
- out_dict = rtlsim_exec(model, inp_dict, pre_hook=rtlsim_pre_hook)
+ (in_npy_all, exp_out_npy_all) = cfg._resolve_verification_io_pair()
+ bsize_in = in_npy_all.shape[0]
+ bsize_out = exp_out_npy_all.shape[0]
+ assert bsize_in == bsize_out, "Batch sizes don't match for verification IO pair"
+ all_res = True
+ for b in range(bsize_in):
+ in_npy = np.expand_dims(in_npy_all[b], axis=0)
+ exp_out_npy = np.expand_dims(exp_out_npy_all[b], axis=0)
+ if need_parent:
+ assert (
+ cfg.save_intermediate_models
+ ), "Enable save_intermediate_models for verification"
+ parent_model_fn = intermediate_models_dir + "/dataflow_parent.onnx"
+ child_model_fn = intermediate_models_dir + "/verify_%s.onnx" % step_name
+ model.save(child_model_fn)
+ parent_model = ModelWrapper(parent_model_fn)
+ out_tensor_name = parent_model.graph.output[0].name
+ exp_ishape = parent_model.get_tensor_shape(parent_model.graph.input[0].name)
+ if in_npy.shape != exp_ishape:
+ print(
+ "Verification input has shape %s while model expects %s"
+ % (str(in_npy.shape), str(exp_ishape))
+ )
+ print("Attempting to force model shape on verification input")
+ in_npy = in_npy.reshape(exp_ishape)
+ out_dict = execute_parent(
+ parent_model_fn, child_model_fn, in_npy, return_full_ctx=True
+ )
+ out_npy = out_dict[out_tensor_name]
else:
- out_dict = execute_onnx(model, inp_dict, True)
- out_npy = out_dict[out_tensor_name]
- res = np.isclose(exp_out_npy, out_npy, atol=1e-3).all()
- res_to_str = {True: "SUCCESS", False: "FAIL"}
- res_str = res_to_str[res]
- if cfg.verify_save_full_context:
- verification_output_fn = verify_out_dir + "/verify_%s_%s.npz" % (
- step_name,
- res_str,
- )
- np.savez(verification_output_fn, **out_dict)
- else:
- verification_output_fn = verify_out_dir + "/verify_%s_%s.npy" % (
- step_name,
- res_str,
- )
- np.save(verification_output_fn, out_npy)
- print("Verification for %s : %s" % (step_name, res_str))
+ inp_tensor_name = model.graph.input[0].name
+ out_tensor_name = model.graph.output[0].name
+ exp_ishape = model.get_tensor_shape(inp_tensor_name)
+ if in_npy.shape != exp_ishape:
+ print(
+ "Verification input has shape %s while model expects %s"
+ % (str(in_npy.shape), str(exp_ishape))
+ )
+ print("Attempting to force model shape on verification input")
+ in_npy = in_npy.reshape(exp_ishape)
+ inp_dict = {inp_tensor_name: in_npy}
+ if rtlsim_pre_hook is not None:
+ out_dict = rtlsim_exec(model, inp_dict, pre_hook=rtlsim_pre_hook)
+ else:
+ out_dict = execute_onnx(model, inp_dict, True)
+ out_npy = out_dict[out_tensor_name]
+ exp_oshape = exp_out_npy.shape
+ if out_npy.shape != exp_oshape:
+ print(
+ "Verification output has shape %s while model produces %s"
+ % (str(exp_oshape), str(out_npy.shape))
+ )
+ print("Attempting to force model shape on verification output")
+ out_npy = out_npy.reshape(exp_oshape)
+
+ res = np.isclose(exp_out_npy, out_npy, atol=1e-3).all()
+ all_res = all_res and res
+ res_to_str = {True: "SUCCESS", False: "FAIL"}
+ res_str = res_to_str[res]
+ if cfg.verify_save_full_context:
+ verification_output_fn = verify_out_dir + "/verify_%s_%d_%s.npz" % (
+ step_name,
+ b,
+ res_str,
+ )
+ np.savez(verification_output_fn, **out_dict)
+ else:
+ verification_output_fn = verify_out_dir + "/verify_%s_%d_%s.npy" % (
+ step_name,
+ b,
+ res_str,
+ )
+ np.save(verification_output_fn, out_npy)
+ print("Verification for %s : %s" % (step_name, res_to_str[all_res]))
def prepare_for_stitched_ip_rtlsim(verify_model, cfg):
--
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