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June 15, 2020 09:36
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--------------------------------------------------------------------------- | |
TypeError Traceback (most recent call last) | |
<ipython-input-3-dc0f2ac96f27> in <module> | |
15 RBM.fit(all_data[in_train][order_train], weights= all_weights[in_train][order_train], batch_size = batch_size, | |
16 n_iter = n_iter, l1b = l1b, N_MC = N_MC, | |
---> 17 decay_after = decay_after, verbose = 0,vverbose=1 ) | |
~/work/PGM/source/rbm.py in fit(self, data, batch_size, learning_rate, extra_params, init, optimizer, batch_norm, CD, N_PT, N_MC, nchains, n_iter, MoI, MoI_h, MoI_tau, PTv, PTh, interpolate_z, degree_interpolate_z, zero_track_RBM, only_sampling, lr_decay, lr_final, decay_after, l1, l1b, l1c, l2, l2_fields, reg_delta, no_fields, weights, adapt_PT, AR_min, adapt_MC, tau_max, update_every, N_PT_max, N_MC_max, from_hidden, learning_rate_multiplier, update_betas, record_acceptance, shuffle_data, epsilon, verbose, vverbose, record, record_interval, data_test, weights_test, l1_custom, l1b_custom, M_AIS, n_betas_AIS, decay_style) | |
704 self.n_v, self.visible, c=self.n_cv) | |
705 else: | |
--> 706 self.fantasy_v = self.vlayer.random_init_config(self.nchains) | |
707 self.fantasy_h = self.hlayer.random_init_config(self.nchains) | |
708 | |
~/work/PGM/source/layer.py in random_init_config(self, n_samples, N_PT) | |
257 return self.sample_from_inputs(np.zeros([N_PT * n_samples, self.N, self.n_c], dtype=curr_float), beta=0).reshape([N_PT, n_samples, self.N]) | |
258 else: | |
--> 259 return self.sample_from_inputs(np.zeros([n_samples, self.N, self.n_c], dtype=curr_float), beta=0).reshape([n_samples, self.N]) | |
260 | |
261 elif self.nature in ['Bernoulli_coupled', 'Spin_coupled']: | |
~/work/PGM/source/layer.py in sample_from_inputs(self, I, I0, beta, out, **kwargs) | |
582 else: | |
583 cy_utilities.sample_from_inputs_Potts_numba2( | |
--> 584 I, self._fields[0, :, :], out) | |
585 return out | |
586 | |
~/anaconda3/lib/python3.7/site-packages/numba/dispatcher.py in _compile_for_args(self, *args, **kws) | |
418 e.patch_message('\n'.join((str(e).rstrip(), help_msg))) | |
419 # ignore the FULL_TRACEBACKS config, this needs reporting! | |
--> 420 raise e | |
421 | |
422 def inspect_llvm(self, signature=None): | |
~/anaconda3/lib/python3.7/site-packages/numba/dispatcher.py in _compile_for_args(self, *args, **kws) | |
351 argtypes.append(self.typeof_pyval(a)) | |
352 try: | |
--> 353 return self.compile(tuple(argtypes)) | |
354 except errors.ForceLiteralArg as e: | |
355 # Received request for compiler re-entry with the list of arguments | |
~/anaconda3/lib/python3.7/site-packages/numba/compiler_lock.py in _acquire_compile_lock(*args, **kwargs) | |
30 def _acquire_compile_lock(*args, **kwargs): | |
31 with self: | |
---> 32 return func(*args, **kwargs) | |
33 return _acquire_compile_lock | |
34 | |
~/anaconda3/lib/python3.7/site-packages/numba/dispatcher.py in compile(self, sig) | |
766 self._cache_misses[sig] += 1 | |
767 try: | |
--> 768 cres = self._compiler.compile(args, return_type) | |
769 except errors.ForceLiteralArg as e: | |
770 def folded(args, kws): | |
~/anaconda3/lib/python3.7/site-packages/numba/dispatcher.py in compile(self, args, return_type) | |
75 | |
76 def compile(self, args, return_type): | |
---> 77 status, retval = self._compile_cached(args, return_type) | |
78 if status: | |
79 return retval | |
~/anaconda3/lib/python3.7/site-packages/numba/dispatcher.py in _compile_cached(self, args, return_type) | |
89 | |
90 try: | |
---> 91 retval = self._compile_core(args, return_type) | |
92 except errors.TypingError as e: | |
93 self._failed_cache[key] = e | |
~/anaconda3/lib/python3.7/site-packages/numba/dispatcher.py in _compile_core(self, args, return_type) | |
107 args=args, return_type=return_type, | |
108 flags=flags, locals=self.locals, | |
--> 109 pipeline_class=self.pipeline_class) | |
110 # Check typing error if object mode is used | |
111 if cres.typing_error is not None and not flags.enable_pyobject: | |
~/anaconda3/lib/python3.7/site-packages/numba/compiler.py in compile_extra(typingctx, targetctx, func, args, return_type, flags, locals, library, pipeline_class) | |
549 pipeline = pipeline_class(typingctx, targetctx, library, | |
550 args, return_type, flags, locals) | |
--> 551 return pipeline.compile_extra(func) | |
552 | |
553 | |
~/anaconda3/lib/python3.7/site-packages/numba/compiler.py in compile_extra(self, func) | |
329 self.state.lifted = () | |
330 self.state.lifted_from = None | |
--> 331 return self._compile_bytecode() | |
332 | |
333 def compile_ir(self, func_ir, lifted=(), lifted_from=None): | |
~/anaconda3/lib/python3.7/site-packages/numba/compiler.py in _compile_bytecode(self) | |
391 """ | |
392 assert self.state.func_ir is None | |
--> 393 return self._compile_core() | |
394 | |
395 def _compile_ir(self): | |
~/anaconda3/lib/python3.7/site-packages/numba/compiler.py in _compile_core(self) | |
371 self.state.status.fail_reason = e | |
372 if is_final_pipeline: | |
--> 373 raise e | |
374 else: | |
375 raise CompilerError("All available pipelines exhausted") | |
~/anaconda3/lib/python3.7/site-packages/numba/compiler.py in _compile_core(self) | |
362 res = None | |
363 try: | |
--> 364 pm.run(self.state) | |
365 if self.state.cr is not None: | |
366 break | |
~/anaconda3/lib/python3.7/site-packages/numba/compiler_machinery.py in run(self, state) | |
345 (self.pipeline_name, pass_desc) | |
346 patched_exception = self._patch_error(msg, e) | |
--> 347 raise patched_exception | |
348 | |
349 def dependency_analysis(self): | |
~/anaconda3/lib/python3.7/site-packages/numba/compiler_machinery.py in run(self, state) | |
336 pass_inst = _pass_registry.get(pss).pass_inst | |
337 if isinstance(pass_inst, CompilerPass): | |
--> 338 self._runPass(idx, pass_inst, state) | |
339 else: | |
340 raise BaseException("Legacy pass in use") | |
~/anaconda3/lib/python3.7/site-packages/numba/compiler_lock.py in _acquire_compile_lock(*args, **kwargs) | |
30 def _acquire_compile_lock(*args, **kwargs): | |
31 with self: | |
---> 32 return func(*args, **kwargs) | |
33 return _acquire_compile_lock | |
34 | |
~/anaconda3/lib/python3.7/site-packages/numba/compiler_machinery.py in _runPass(self, index, pss, internal_state) | |
300 mutated |= check(pss.run_initialization, internal_state) | |
301 with SimpleTimer() as pass_time: | |
--> 302 mutated |= check(pss.run_pass, internal_state) | |
303 with SimpleTimer() as finalize_time: | |
304 mutated |= check(pss.run_finalizer, internal_state) | |
~/anaconda3/lib/python3.7/site-packages/numba/compiler_machinery.py in check(func, compiler_state) | |
273 | |
274 def check(func, compiler_state): | |
--> 275 mangled = func(compiler_state) | |
276 if mangled not in (True, False): | |
277 msg = ("CompilerPass implementations should return True/False. " | |
~/anaconda3/lib/python3.7/site-packages/numba/typed_passes.py in run_pass(self, state) | |
267 state.flags, | |
268 state.parfor_diagnostics) | |
--> 269 parfor_pass.run() | |
270 | |
271 # check the parfor pass worked and warn if it didn't | |
~/anaconda3/lib/python3.7/site-packages/numba/parfor.py in run(self) | |
1498 # run array analysis, a pre-requisite for parfor translation | |
1499 remove_dels(self.func_ir.blocks) | |
-> 1500 self.array_analysis.run(self.func_ir.blocks) | |
1501 # run stencil translation to parfor | |
1502 if self.options.stencil: | |
~/anaconda3/lib/python3.7/site-packages/numba/array_analysis.py in run(self, blocks, equiv_set) | |
1076 inst = ir.SetItem(inst.target, inst.index_var, inst.value, inst.loc) | |
1077 self.calltypes[inst] = orig_calltype | |
-> 1078 pre, post = self._analyze_inst(label, scope, equiv_set, inst, redefined) | |
1079 # Remove anything multiply defined in this block from every block equivs. | |
1080 if len(redefined) > 0: | |
~/anaconda3/lib/python3.7/site-packages/numba/array_analysis.py in _analyze_inst(self, label, scope, equiv_set, inst, redefined) | |
1119 shape = () | |
1120 elif isinstance(inst.value, ir.Expr): | |
-> 1121 result = self._analyze_expr(scope, equiv_set, inst.value) | |
1122 if result: | |
1123 shape = result[0] | |
~/anaconda3/lib/python3.7/site-packages/numba/array_analysis.py in _analyze_expr(self, scope, equiv_set, expr) | |
1294 except AttributeError: | |
1295 return None | |
-> 1296 return guard(fn, scope, equiv_set, expr) | |
1297 | |
1298 def _analyze_op_getattr(self, scope, equiv_set, expr): | |
~/anaconda3/lib/python3.7/site-packages/numba/ir_utils.py in guard(func, *args, **kwargs) | |
1435 """ | |
1436 try: | |
-> 1437 return func(*args, **kwargs) | |
1438 except GuardException: | |
1439 return None | |
~/anaconda3/lib/python3.7/site-packages/numba/array_analysis.py in _analyze_op_inplace_binop(self, scope, equiv_set, expr) | |
1703 def _analyze_op_inplace_binop(self, scope, equiv_set, expr): | |
1704 require(expr.fn in INPLACE_BINARY_MAP_OP) | |
-> 1705 return self._analyze_broadcast(scope, equiv_set, expr.loc, [expr.lhs, expr.rhs]) | |
1706 | |
1707 def _analyze_op_arrayexpr(self, scope, equiv_set, expr): | |
~/anaconda3/lib/python3.7/site-packages/numba/array_analysis.py in _analyze_broadcast(self, scope, equiv_set, loc, args) | |
2285 except GuardException: | |
2286 return arrs[0], self._call_assert_equiv(scope, loc, equiv_set, arrs) | |
-> 2287 return self._broadcast_assert_shapes(scope, equiv_set, loc, shapes, names) | |
2288 | |
2289 def _broadcast_assert_shapes(self, scope, equiv_set, loc, shapes, names): | |
~/anaconda3/lib/python3.7/site-packages/numba/array_analysis.py in _broadcast_assert_shapes(self, scope, equiv_set, loc, shapes, names) | |
2293 asserts = [] | |
2294 new_shape = [] | |
-> 2295 max_dim = max([len(shape) for shape in shapes]) | |
2296 const_size_one = None | |
2297 for i in range(max_dim): | |
~/anaconda3/lib/python3.7/site-packages/numba/array_analysis.py in <listcomp>(.0) | |
2293 asserts = [] | |
2294 new_shape = [] | |
-> 2295 max_dim = max([len(shape) for shape in shapes]) | |
2296 const_size_one = None | |
2297 for i in range(max_dim): | |
TypeError: Failed in nopython mode pipeline (step: convert to parfors) | |
object of type 'NoneType' has no len() |
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