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llvm: Add more structure stat messages #2729

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merged 3 commits into from
Jul 11, 2023
Merged

llvm: Add more structure stat messages #2729

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caa4802
llvm/execution: Use "state" instead of context/CTX in debug print
jvesely Jul 11, 2023
66124db
llvm/execution: Print information about composition input struct if e…
jvesely Jul 11, 2023
3265c9b
llvm/execution: Print information about "evaluate" output structure i…
jvesely Jul 11, 2023
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15 changes: 13 additions & 2 deletions psyneulink/core/llvm/execution.py
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Original file line number Diff line number Diff line change
Expand Up @@ -573,7 +573,7 @@ def execute_node(self, node, inputs=None, context=None):
inputs, self.__frozen_vals, self._data_struct)

if "comp_node_debug" in self._debug_env:
print("RAN: {}. CTX: {}".format(node, self.extract_node_state(node)))
print("RAN: {}. State: {}".format(node, self.extract_node_state(node)))
print("RAN: {}. Params: {}".format(node, self.extract_node_params(node)))
print("RAN: {}. Results: {}".format(node, self.extract_node_output(node)))

Expand Down Expand Up @@ -635,7 +635,13 @@ def _get_run_input_struct(self, inputs, num_input_sets, arg=3):
assert len(inputs) == len(self._execution_contexts)
# Extract input for each trial and execution id
run_inputs = ((([x] for x in self._composition._build_variable_for_input_CIM({k:v[i] for k,v in inp.items()})) for i in range(num_input_sets)) for inp in inputs)
return c_input(*_tupleize(run_inputs))
c_inputs = c_input(*_tupleize(run_inputs))
if "stat" in self._debug_env:
print("Instantiated struct: input ( size:" ,
_pretty_size(ctypes.sizeof(c_inputs)), ")",
"for", self._obj.name)

return c_inputs

def _get_generator_run_input_struct(self, inputs, runs):
assert len(self._execution_contexts) == 1
Expand Down Expand Up @@ -772,6 +778,11 @@ def _prepare_evaluate(self, inputs, num_input_sets, num_evaluations, all_results
out_ty = out_el_ty * num_evaluations

ct_num_inputs = bin_func.byref_arg_types[7](num_input_sets)
if "stat" in self._debug_env:
print("Evaluate result struct type size:",
_pretty_size(ctypes.sizeof(out_ty)),
"( evaluations:", num_evaluations, "element size:", ctypes.sizeof(out_el_ty), ")",
"for", self._obj.name)

# return variable as numpy array. pycuda can use it directly
return ct_comp_param, ct_comp_state, ct_comp_data, ct_inputs, out_ty, ct_num_inputs
Expand Down
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