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d:\python\python384r1\lib\site-packages\theano\graph\op.py in call(self, *inputs, **kwargs)
251
252 if config.compute_test_value != "off":
--> 253 compute_test_value(node)
254
255 if self.default_output is not None:
d:\python\python384r1\lib\site-packages\theano\graph\op.py in compute_test_value(node)
124
125 # Create a thunk that performs the computation
--> 126 thunk = node.op.make_thunk(node, storage_map, compute_map, no_recycling=[])
127 thunk.inputs = [storage_map[v] for v in node.inputs]
128 thunk.outputs = [storage_map[v] for v in node.outputs]
d:\python\python384r1\lib\site-packages\theano\graph\op.py in make_thunk(self, node, storage_map, compute_map, no_recycling, impl)
632 )
633 try:
--> 634 return self.make_c_thunk(node, storage_map, compute_map, no_recycling)
635 except (NotImplementedError, MethodNotDefined):
636 # We requested the c code, so don't catch the error.
d:\python\python384r1\lib\site-packages\theano\graph\op.py in make_c_thunk(self, node, storage_map, compute_map, no_recycling)
598 print(f"Disabling C code for {self} due to unsupported float16")
599 raise NotImplementedError("float16")
--> 600 outputs = cl.make_thunk(
601 input_storage=node_input_storage, output_storage=node_output_storage
602 )
PyMC3, python 3.84, win10, Jupyter-lab
code from Chap1 Sec: Introducing our first hammer: PyMC3,
import pymc3 as pm
import theano.tensor as tt
with pm.Model() as model:
alpha = 1.0/count_data.mean() # Recall count_data is the
# variable that holds our txt counts
lambda_1 = pm.Exponential("lambda_1", alpha)
lambda_2 = pm.Exponential("lambda_2", alpha)
Error:
Exception Traceback (most recent call last)
in
5 alpha = 1.0/count_data.mean() # Recall count_data is the
6 # variable that holds our txt counts
----> 7 lambda_1 = pm.Exponential("lambda_1", alpha)
8 lambda_2 = pm.Exponential("lambda_2", alpha)
9
d:\python\python384r1\lib\site-packages\pymc3\distributions\distribution.py in new(cls, name, *args, **kwargs)
119 dist = cls.dist(*args, **kwargs, shape=shape)
120 else:
--> 121 dist = cls.dist(*args, **kwargs)
122 return model.Var(name, dist, data, total_size, dims=dims)
123
d:\python\python384r1\lib\site-packages\pymc3\distributions\distribution.py in dist(cls, *args, **kwargs)
128 def dist(cls, *args, **kwargs):
129 dist = object.new(cls)
--> 130 dist.init(*args, **kwargs)
131 return dist
132
d:\python\python384r1\lib\site-packages\pymc3\distributions\continuous.py in init(self, lam, *args, **kwargs)
1485 super().init(*args, **kwargs)
1486 self.lam = lam = tt.as_tensor_variable(floatX(lam))
-> 1487 self.mean = 1.0 / self.lam
1488 self.median = self.mean * tt.log(2)
1489 self.mode = tt.zeros_like(self.lam)
d:\python\python384r1\lib\site-packages\theano\tensor\var.py in rtruediv(self, other)
174
175 def rtruediv(self, other):
--> 176 return theano.tensor.basic.true_div(other, self)
177
178 def rfloordiv(self, other):
d:\python\python384r1\lib\site-packages\theano\graph\op.py in call(self, *inputs, **kwargs)
251
252 if config.compute_test_value != "off":
--> 253 compute_test_value(node)
254
255 if self.default_output is not None:
d:\python\python384r1\lib\site-packages\theano\graph\op.py in compute_test_value(node)
124
125 # Create a thunk that performs the computation
--> 126 thunk = node.op.make_thunk(node, storage_map, compute_map, no_recycling=[])
127 thunk.inputs = [storage_map[v] for v in node.inputs]
128 thunk.outputs = [storage_map[v] for v in node.outputs]
d:\python\python384r1\lib\site-packages\theano\graph\op.py in make_thunk(self, node, storage_map, compute_map, no_recycling, impl)
632 )
633 try:
--> 634 return self.make_c_thunk(node, storage_map, compute_map, no_recycling)
635 except (NotImplementedError, MethodNotDefined):
636 # We requested the c code, so don't catch the error.
d:\python\python384r1\lib\site-packages\theano\graph\op.py in make_c_thunk(self, node, storage_map, compute_map, no_recycling)
598 print(f"Disabling C code for {self} due to unsupported float16")
599 raise NotImplementedError("float16")
--> 600 outputs = cl.make_thunk(
601 input_storage=node_input_storage, output_storage=node_output_storage
602 )
d:\python\python384r1\lib\site-packages\theano\link\c\basic.py in make_thunk(self, input_storage, output_storage, storage_map)
1201 """
1202 init_tasks, tasks = self.get_init_tasks()
-> 1203 cthunk, module, in_storage, out_storage, error_storage = self.compile(
1204 input_storage, output_storage, storage_map
1205 )
d:\python\python384r1\lib\site-packages\theano\link\c\basic.py in compile(self, input_storage, output_storage, storage_map)
1136 input_storage = tuple(input_storage)
1137 output_storage = tuple(output_storage)
-> 1138 thunk, module = self.cthunk_factory(
1139 error_storage,
1140 input_storage,
d:\python\python384r1\lib\site-packages\theano\link\c\basic.py in cthunk_factory(self, error_storage, in_storage, out_storage, storage_map)
1632 for node in self.node_order:
1633 node.op.prepare_node(node, storage_map, None, "c")
-> 1634 module = get_module_cache().module_from_key(key=key, lnk=self)
1635
1636 vars = self.inputs + self.outputs + self.orphans
d:\python\python384r1\lib\site-packages\theano\link\c\cmodule.py in module_from_key(self, key, lnk)
1189 try:
1190 location = dlimport_workdir(self.dirname)
-> 1191 module = lnk.compile_cmodule(location)
1192 name = module.file
1193 assert name.startswith(location)
d:\python\python384r1\lib\site-packages\theano\link\c\basic.py in compile_cmodule(self, location)
1541 try:
1542 _logger.debug(f"LOCATION {location}")
-> 1543 module = c_compiler.compile_str(
1544 module_name=mod.code_hash,
1545 src_code=src_code,
d:\python\python384r1\lib\site-packages\theano\link\c\cmodule.py in compile_str(module_name, src_code, location, include_dirs, lib_dirs, libs, preargs, py_module, hide_symbols)
2544 # difficult to read.
2545 compile_stderr = compile_stderr.replace("\n", ". ")
-> 2546 raise Exception(
2547 f"Compilation failed (return status={status}): {compile_stderr}"
2548 )
Exception: ('Compilation failed (return status=1): d:\python\python384r1\libs/python38.lib: error adding symbols: File in wrong format\r. collect2.exe: error: ld returned 1 exit status\r. ', 'FunctionGraph(Elemwise{true_div,no_inplace}(TensorConstant{1.0}, TensorConstant{0.05065023956194388}))')
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