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example.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"from scipy import stats as sps\n",
"import pymc3 as pm\n",
"from prefect import task, Flow\n",
"from prefect.engine.executors import DaskExecutor, LocalDaskExecutor"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"@task\n",
"def flip_coin(p):\n",
" return sps.bernoulli(p=p).rvs(1000, random_state=42)\n",
"\n",
"@task\n",
"def infer_p(samples):\n",
" with pm.Model() as model:\n",
" bias = pm.Beta('bias', 1, 1)\n",
" coin = pm.Bernoulli('coin', p=bias, observed=samples)\n",
" trace = pm.sample(tune=1500, target_accept=.9, chains=1, cores=1)\n",
" print(trace['bias'].mean())"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[2020-04-28 15:17:56] INFO - prefect.FlowRunner | Beginning Flow run for 'CoinFlow'\n",
"[2020-04-28 15:17:56] INFO - prefect.FlowRunner | Starting flow run.\n",
"[2020-04-28 15:17:57] INFO - prefect.TaskRunner | Task 'flip_coin': Starting task run...\n",
"[2020-04-28 15:17:57] INFO - prefect.TaskRunner | Task 'flip_coin': finished task run for task with final state: 'Success'\n",
"[2020-04-28 15:17:57] INFO - prefect.TaskRunner | Task 'infer_p': Starting task run...\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"Auto-assigning NUTS sampler...\n",
"Initializing NUTS using jitter+adapt_diag...\n",
"Sequential sampling (1 chains in 1 job)\n",
"NUTS: [bias]\n"
]
},
{
"data": {
"text/html": [
"\n",
" <div>\n",
" <style>\n",
" /* Turns off some styling */\n",
" progress {\n",
" /* gets rid of default border in Firefox and Opera. */\n",
" border: none;\n",
" /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
" background-size: auto;\n",
" }\n",
" .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
" background: #F44336;\n",
" }\n",
" </style>\n",
" <progress value='2500' class='' max='2500', style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
" 100.00% [2500/2500 00:02<00:00 Sampling chain 0, 0 divergences]\n",
" </div>\n",
" "
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"Sampling 1 chain for 1_500 tune and 1_000 draw iterations (1_500 + 1_000 draws total) took 3 seconds.\n",
"Only one chain was sampled, this makes it impossible to run some convergence checks\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"0.4976689139171085\n",
"[2020-04-28 15:18:12] INFO - prefect.TaskRunner | Task 'infer_p': finished task run for task with final state: 'Success'\n",
"[2020-04-28 15:18:12] INFO - prefect.FlowRunner | Flow run SUCCESS: all reference tasks succeeded\n"
]
}
],
"source": [
"# Single value\n",
"with Flow('CoinFlow') as flow:\n",
" flips = flip_coin(.5)\n",
" infer_p(flips)\n",
"\n",
" flow.run()"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[2020-04-28 16:26:58] INFO - prefect.FlowRunner | Beginning Flow run for 'CoinFlow'\n",
"[2020-04-28 16:26:58] INFO - prefect.FlowRunner | Starting flow run.\n",
"[2020-04-28 16:26:58] INFO - prefect.TaskRunner | Task 'flip_coin': Starting task run...\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/Users/twiecki/miniconda3/envs/pymc3/lib/python3.7/site-packages/distributed/node.py:244: UserWarning: Port 8787 is already in use.\n",
"Perhaps you already have a cluster running?\n",
"Hosting the HTTP server on port 59233 instead\n",
" http_address[\"port\"], self.http_server.port\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"[2020-04-28 16:26:58] INFO - prefect.TaskRunner | Task 'flip_coin[0]': Starting task run...\n",
"[2020-04-28 16:26:58] INFO - prefect.TaskRunner | Task 'flip_coin[1]': Starting task run...\n",
"[2020-04-28 16:26:58] INFO - prefect.TaskRunner | Task 'flip_coin[0]': finished task run for task with final state: 'Success'\n",
"[2020-04-28 16:26:58] INFO - prefect.TaskRunner | Task 'flip_coin[1]': finished task run for task with final state: 'Success'\n",
"[2020-04-28 16:26:58] INFO - prefect.TaskRunner | Task 'flip_coin': finished task run for task with final state: 'Mapped'\n",
"[2020-04-28 16:26:58] INFO - prefect.TaskRunner | Task 'infer_p': Starting task run...\n",
"[2020-04-28 16:26:58] INFO - prefect.TaskRunner | Task 'infer_p[1]': Starting task run...\n",
"[2020-04-28 16:26:58] INFO - prefect.TaskRunner | Task 'infer_p[0]': Starting task run...\n",
"[2020-04-28 16:26:59] ERROR - prefect.TaskRunner | Unexpected error: ValueError('Cannot compute test value: input 0 (Elemwise{neg,no_inplace}.0) of Op Elemwise{log1p,no_inplace}(Elemwise{neg,no_inplace}.0) missing default value. \\nBacktrace when that variable is created:\\n\\n File \"<ipython-input-2-59b546126d39>\", line 8, in infer_p\\n bias = pm.Beta(\\'bias\\', 1, 1)\\n File \"/Users/twiecki/working/projects/pymc/pymc3/distributions/distribution.py\", line 66, in __new__\\n return model.Var(name, dist, data, total_size)\\n File \"/Users/twiecki/working/projects/pymc/pymc3/model.py\", line 1005, in Var\\n model=self)\\n File \"/Users/twiecki/working/projects/pymc/pymc3/model.py\", line 1743, in __init__\\n transformed_name, transform.apply(distribution), total_size=total_size)\\n File \"/Users/twiecki/working/projects/pymc/pymc3/model.py\", line 998, in Var\\n total_size=total_size, model=self)\\n File \"/Users/twiecki/working/projects/pymc/pymc3/model.py\", line 1459, in __init__\\n self.logp_nojac_unscaledt = distribution.logp_nojac(self)\\n File \"/Users/twiecki/working/projects/pymc/pymc3/distributions/transforms.py\", line 197, in logp_nojac\\n return self.dist.logp(self.transform_used.backward(x))\\n File \"/Users/twiecki/working/projects/pymc/pymc3/distributions/continuous.py\", line 1315, in logp\\n log1pval = tt.log1p(-value)\\n')\n",
"Traceback (most recent call last):\n",
" File \"/Users/twiecki/miniconda3/envs/pymc3/lib/python3.7/site-packages/theano/gof/op.py\", line 625, in __call__\n",
" storage_map[ins] = [self._get_test_value(ins)]\n",
" File \"/Users/twiecki/miniconda3/envs/pymc3/lib/python3.7/site-packages/theano/gof/op.py\", line 581, in _get_test_value\n",
" raise AttributeError('%s has no test value %s' % (v, detailed_err_msg))\n",
"AttributeError: Elemwise{neg,no_inplace}.0 has no test value \n",
"Backtrace when that variable is created:\n",
"\n",
" File \"<ipython-input-2-59b546126d39>\", line 8, in infer_p\n",
" bias = pm.Beta('bias', 1, 1)\n",
" File \"/Users/twiecki/working/projects/pymc/pymc3/distributions/distribution.py\", line 66, in __new__\n",
" return model.Var(name, dist, data, total_size)\n",
" File \"/Users/twiecki/working/projects/pymc/pymc3/model.py\", line 1005, in Var\n",
" model=self)\n",
" File \"/Users/twiecki/working/projects/pymc/pymc3/model.py\", line 1743, in __init__\n",
" transformed_name, transform.apply(distribution), total_size=total_size)\n",
" File \"/Users/twiecki/working/projects/pymc/pymc3/model.py\", line 998, in Var\n",
" total_size=total_size, model=self)\n",
" File \"/Users/twiecki/working/projects/pymc/pymc3/model.py\", line 1459, in __init__\n",
" self.logp_nojac_unscaledt = distribution.logp_nojac(self)\n",
" File \"/Users/twiecki/working/projects/pymc/pymc3/distributions/transforms.py\", line 197, in logp_nojac\n",
" return self.dist.logp(self.transform_used.backward(x))\n",
" File \"/Users/twiecki/working/projects/pymc/pymc3/distributions/continuous.py\", line 1315, in logp\n",
" log1pval = tt.log1p(-value)\n",
"\n",
"\n",
"During handling of the above exception, another exception occurred:\n",
"\n",
"Traceback (most recent call last):\n",
" File \"/Users/twiecki/miniconda3/envs/pymc3/lib/python3.7/site-packages/prefect/engine/runner.py\", line 48, in inner\n",
" new_state = method(self, state, *args, **kwargs)\n",
" File \"/Users/twiecki/miniconda3/envs/pymc3/lib/python3.7/site-packages/prefect/engine/task_runner.py\", line 884, in get_task_run_state\n",
" self.task.run, timeout=self.task.timeout, **raw_inputs\n",
" File \"/Users/twiecki/miniconda3/envs/pymc3/lib/python3.7/site-packages/prefect/utilities/executors.py\", line 182, in timeout_handler\n",
" return fn(*args, **kwargs)\n",
" File \"<ipython-input-2-59b546126d39>\", line 8, in infer_p\n",
" bias = pm.Beta('bias', 1, 1)\n",
" File \"/Users/twiecki/working/projects/pymc/pymc3/distributions/distribution.py\", line 66, in __new__\n",
" return model.Var(name, dist, data, total_size)\n",
" File \"/Users/twiecki/working/projects/pymc/pymc3/model.py\", line 1005, in Var\n",
" model=self)\n",
" File \"/Users/twiecki/working/projects/pymc/pymc3/model.py\", line 1743, in __init__\n",
" transformed_name, transform.apply(distribution), total_size=total_size)\n",
" File \"/Users/twiecki/working/projects/pymc/pymc3/model.py\", line 998, in Var\n",
" total_size=total_size, model=self)\n",
" File \"/Users/twiecki/working/projects/pymc/pymc3/model.py\", line 1459, in __init__\n",
" self.logp_nojac_unscaledt = distribution.logp_nojac(self)\n",
" File \"/Users/twiecki/working/projects/pymc/pymc3/distributions/transforms.py\", line 197, in logp_nojac\n",
" return self.dist.logp(self.transform_used.backward(x))\n",
" File \"/Users/twiecki/working/projects/pymc/pymc3/distributions/continuous.py\", line 1315, in logp\n",
" log1pval = tt.log1p(-value)\n",
" File \"/Users/twiecki/miniconda3/envs/pymc3/lib/python3.7/site-packages/theano/gof/op.py\", line 639, in __call__\n",
" (i, ins, node, detailed_err_msg))\n",
"ValueError: Cannot compute test value: input 0 (Elemwise{neg,no_inplace}.0) of Op Elemwise{log1p,no_inplace}(Elemwise{neg,no_inplace}.0) missing default value. \n",
"Backtrace when that variable is created:\n",
"\n",
" File \"<ipython-input-2-59b546126d39>\", line 8, in infer_p\n",
" bias = pm.Beta('bias', 1, 1)\n",
" File \"/Users/twiecki/working/projects/pymc/pymc3/distributions/distribution.py\", line 66, in __new__\n",
" return model.Var(name, dist, data, total_size)\n",
" File \"/Users/twiecki/working/projects/pymc/pymc3/model.py\", line 1005, in Var\n",
" model=self)\n",
" File \"/Users/twiecki/working/projects/pymc/pymc3/model.py\", line 1743, in __init__\n",
" transformed_name, transform.apply(distribution), total_size=total_size)\n",
" File \"/Users/twiecki/working/projects/pymc/pymc3/model.py\", line 998, in Var\n",
" total_size=total_size, model=self)\n",
" File \"/Users/twiecki/working/projects/pymc/pymc3/model.py\", line 1459, in __init__\n",
" self.logp_nojac_unscaledt = distribution.logp_nojac(self)\n",
" File \"/Users/twiecki/working/projects/pymc/pymc3/distributions/transforms.py\", line 197, in logp_nojac\n",
" return self.dist.logp(self.transform_used.backward(x))\n",
" File \"/Users/twiecki/working/projects/pymc/pymc3/distributions/continuous.py\", line 1315, in logp\n",
" log1pval = tt.log1p(-value)\n",
"\n",
"[2020-04-28 16:26:59] INFO - prefect.TaskRunner | Task 'infer_p[1]': finished task run for task with final state: 'Failed'\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"Auto-assigning NUTS sampler...\n",
"Initializing NUTS using jitter+adapt_diag...\n",
"Sequential sampling (1 chains in 1 job)\n",
"NUTS: [bias]\n"
]
},
{
"data": {
"text/html": [
"\n",
" <div>\n",
" <style>\n",
" /* Turns off some styling */\n",
" progress {\n",
" /* gets rid of default border in Firefox and Opera. */\n",
" border: none;\n",
" /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
" background-size: auto;\n",
" }\n",
" .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
" background: #F44336;\n",
" }\n",
" </style>\n",
" <progress value='2500' class='' max='2500', style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
" 100.00% [2500/2500 00:02<00:00 Sampling chain 0, 0 divergences]\n",
" </div>\n",
" "
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"Sampling 1 chain for 1_500 tune and 1_000 draw iterations (1_500 + 1_000 draws total) took 2 seconds.\n",
"Only one chain was sampled, this makes it impossible to run some convergence checks\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"0.4969830636996289\n",
"[2020-04-28 16:27:02] INFO - prefect.TaskRunner | Task 'infer_p[0]': finished task run for task with final state: 'Success'\n",
"[2020-04-28 16:27:02] INFO - prefect.TaskRunner | Task 'infer_p': finished task run for task with final state: 'Mapped'\n",
"[2020-04-28 16:27:05] INFO - prefect.FlowRunner | Flow run FAILED: some reference tasks failed.\n"
]
}
],
"source": [
"# Map over two coins\n",
"with Flow('CoinFlow') as flow:\n",
" flips = flip_coin.map([.5, .25])\n",
" infer_p.map(flips)\n",
" flow.run(executor=DaskExecutor(n_workers=4, threads_per_worker=1))"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[2020-04-28 15:03:38] INFO - prefect.FlowRunner | Beginning Flow run for 'CoinFlow'\n",
"[2020-04-28 15:03:38] INFO - prefect.FlowRunner | Starting flow run.\n",
"[2020-04-28 15:03:38] INFO - prefect.TaskRunner | Task 'flip_coin': Starting task run...\n",
"[2020-04-28 15:03:38] INFO - prefect.TaskRunner | Task 'flip_coin[0]': Starting task run...\n",
"[2020-04-28 15:03:38] INFO - prefect.TaskRunner | Task 'flip_coin[1]': Starting task run...\n",
"[2020-04-28 15:03:38] INFO - prefect.TaskRunner | Task 'flip_coin[0]': finished task run for task with final state: 'Success'\n",
"[2020-04-28 15:03:38] INFO - prefect.TaskRunner | Task 'flip_coin[1]': finished task run for task with final state: 'Success'\n",
"[2020-04-28 15:03:38] INFO - prefect.TaskRunner | Task 'flip_coin': finished task run for task with final state: 'Mapped'\n",
"[2020-04-28 15:03:38] INFO - prefect.TaskRunner | Task 'infer_p': Starting task run...\n",
"[2020-04-28 15:03:38] INFO - prefect.TaskRunner | Task 'infer_p[0]': Starting task run...\n",
"[2020-04-28 15:03:38] INFO - prefect.TaskRunner | Task 'infer_p[1]': Starting task run...\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"Auto-assigning NUTS sampler...\n",
"Initializing NUTS using jitter+adapt_diag...\n",
"Auto-assigning NUTS sampler...\n",
"Initializing NUTS using jitter+adapt_diag...\n",
"Multiprocess sampling (2 chains in 2 jobs)\n",
"Multiprocess sampling (2 chains in 2 jobs)\n",
"NUTS: [bias]\n",
"NUTS: [bias]\n",
"ERROR (theano.gof.opt): Optimization failure due to: local_upcast_elemwise_constant_inputs\n",
"ERROR (theano.gof.opt): node: Elemwise{add,no_inplace}(TensorConstant{1.0}, Elemwise{exp,no_inplace}.0)\n",
"ERROR (theano.gof.opt): TRACEBACK:\n",
"ERROR (theano.gof.opt): Traceback (most recent call last):\n",
" File \"/Users/twiecki/miniconda3/envs/pymc3py38/lib/python3.8/site-packages/theano/gof/op.py\", line 625, in __call__\n",
" storage_map[ins] = [self._get_test_value(ins)]\n",
" File \"/Users/twiecki/miniconda3/envs/pymc3py38/lib/python3.8/site-packages/theano/gof/op.py\", line 581, in _get_test_value\n",
" raise AttributeError('%s has no test value %s' % (v, detailed_err_msg))\n",
"AttributeError: Elemwise{Cast{float64}}.0 has no test value \n",
"\n",
"During handling of the above exception, another exception occurred:\n",
"\n",
"Traceback (most recent call last):\n",
" File \"/Users/twiecki/miniconda3/envs/pymc3py38/lib/python3.8/site-packages/theano/gof/opt.py\", line 2034, in process_node\n",
" replacements = lopt.transform(node)\n",
" File \"/Users/twiecki/miniconda3/envs/pymc3py38/lib/python3.8/site-packages/theano/tensor/opt.py\", line 2522, in local_upcast_elemwise_constant_inputs\n",
" new_inputs.append(T.shape_padleft(\n",
" File \"/Users/twiecki/miniconda3/envs/pymc3py38/lib/python3.8/site-packages/theano/tensor/basic.py\", line 4572, in shape_padleft\n",
" return DimShuffle(_t.broadcastable, pattern)(_t)\n",
" File \"/Users/twiecki/miniconda3/envs/pymc3py38/lib/python3.8/site-packages/theano/gof/op.py\", line 637, in __call__\n",
" raise ValueError(\n",
"ValueError: Cannot compute test value: input 0 (Elemwise{Cast{float64}}.0) of Op InplaceDimShuffle{}(Elemwise{Cast{float64}}.0) missing default value. \n",
"\n",
"ERROR (theano.gof.opt): Optimization failure due to: local_upcast_elemwise_constant_inputs\n",
"ERROR (theano.gof.opt): node: Elemwise{add,no_inplace}(Elemwise{true_div,no_inplace}.0, TensorConstant{0.0})\n",
"ERROR (theano.gof.opt): TRACEBACK:\n",
"ERROR (theano.gof.opt): Traceback (most recent call last):\n",
" File \"/Users/twiecki/miniconda3/envs/pymc3py38/lib/python3.8/site-packages/theano/gof/op.py\", line 625, in __call__\n",
" storage_map[ins] = [self._get_test_value(ins)]\n",
" File \"/Users/twiecki/miniconda3/envs/pymc3py38/lib/python3.8/site-packages/theano/gof/op.py\", line 581, in _get_test_value\n",
" raise AttributeError('%s has no test value %s' % (v, detailed_err_msg))\n",
"AttributeError: Elemwise{Cast{float64}}.0 has no test value \n",
"\n",
"During handling of the above exception, another exception occurred:\n",
"\n",
"Traceback (most recent call last):\n",
" File \"/Users/twiecki/miniconda3/envs/pymc3py38/lib/python3.8/site-packages/theano/gof/opt.py\", line 2034, in process_node\n",
" replacements = lopt.transform(node)\n",
" File \"/Users/twiecki/miniconda3/envs/pymc3py38/lib/python3.8/site-packages/theano/tensor/opt.py\", line 2522, in local_upcast_elemwise_constant_inputs\n",
" new_inputs.append(T.shape_padleft(\n",
" File \"/Users/twiecki/miniconda3/envs/pymc3py38/lib/python3.8/site-packages/theano/tensor/basic.py\", line 4572, in shape_padleft\n",
" return DimShuffle(_t.broadcastable, pattern)(_t)\n",
" File \"/Users/twiecki/miniconda3/envs/pymc3py38/lib/python3.8/site-packages/theano/gof/op.py\", line 637, in __call__\n",
" raise ValueError(\n",
"ValueError: Cannot compute test value: input 0 (Elemwise{Cast{float64}}.0) of Op InplaceDimShuffle{}(Elemwise{Cast{float64}}.0) missing default value. \n",
"\n",
"<<!! BUG IN FGRAPH.REPLACE OR A LISTENER !!>> <class 'theano.gof.fg.CachedConstantError'> You manually constructed a FunctionGraph, but you passed it a graph that has a cached constant. This should not happen. Clone the graph before building the FunctionGraph. local_upcast_elemwise_constant_inputs\n",
"ERROR (theano.gof.opt): Optimization failure due to: local_upcast_elemwise_constant_inputs\n",
"ERROR (theano.gof.opt): node: Elemwise{add,no_inplace}(TensorConstant{1.0}, Elemwise{exp,no_inplace}.0)\n",
"ERROR (theano.gof.opt): TRACEBACK:\n",
"ERROR (theano.gof.opt): Traceback (most recent call last):\n",
" File \"/Users/twiecki/miniconda3/envs/pymc3py38/lib/python3.8/site-packages/theano/gof/opt.py\", line 2072, in process_node\n",
" fgraph.replace_all_validate_remove(repl_pairs,\n",
" File \"/Users/twiecki/miniconda3/envs/pymc3py38/lib/python3.8/site-packages/theano/gof/toolbox.py\", line 569, in replace_all_validate_remove\n",
" chk = fgraph.replace_all_validate(replacements, reason)\n",
" File \"/Users/twiecki/miniconda3/envs/pymc3py38/lib/python3.8/site-packages/theano/gof/toolbox.py\", line 518, in replace_all_validate\n",
" fgraph.replace(r, new_r, reason=reason, verbose=False)\n",
" File \"/Users/twiecki/miniconda3/envs/pymc3py38/lib/python3.8/site-packages/theano/gof/fg.py\", line 514, in replace\n",
" self.change_input(node, i, new_r, reason=reason)\n",
" File \"/Users/twiecki/miniconda3/envs/pymc3py38/lib/python3.8/site-packages/theano/gof/fg.py\", line 445, in change_input\n",
" self.__import_r__(new_r, reason=reason)\n",
" File \"/Users/twiecki/miniconda3/envs/pymc3py38/lib/python3.8/site-packages/theano/gof/fg.py\", line 346, in __import_r__\n",
" self.__import__(variable.owner, reason=reason)\n",
" File \"/Users/twiecki/miniconda3/envs/pymc3py38/lib/python3.8/site-packages/theano/gof/fg.py\", line 405, in __import__\n",
" self.__setup_r__(input)\n",
" File \"/Users/twiecki/miniconda3/envs/pymc3py38/lib/python3.8/site-packages/theano/gof/fg.py\", line 192, in __setup_r__\n",
" raise CachedConstantError(\n",
"theano.gof.fg.CachedConstantError: You manually constructed a FunctionGraph, but you passed it a graph that has a cached constant. This should not happen. Clone the graph before building the FunctionGraph.\n",
"\n",
"<<!! BUG IN FGRAPH.REPLACE OR A LISTENER !!>> <class 'AssertionError'> local_add_canonizer\n",
"ERROR (theano.gof.opt): Optimization failure due to: local_add_canonizer\n",
"ERROR (theano.gof.opt): node: Elemwise{add,no_inplace}(TensorConstant{1.0}, Elemwise{exp,no_inplace}.0)\n",
"ERROR (theano.gof.opt): TRACEBACK:\n",
"ERROR (theano.gof.opt): Traceback (most recent call last):\n",
" File \"/Users/twiecki/miniconda3/envs/pymc3py38/lib/python3.8/site-packages/theano/gof/opt.py\", line 2072, in process_node\n",
" fgraph.replace_all_validate_remove(repl_pairs,\n",
" File \"/Users/twiecki/miniconda3/envs/pymc3py38/lib/python3.8/site-packages/theano/gof/toolbox.py\", line 569, in replace_all_validate_remove\n",
" chk = fgraph.replace_all_validate(replacements, reason)\n",
" File \"/Users/twiecki/miniconda3/envs/pymc3py38/lib/python3.8/site-packages/theano/gof/toolbox.py\", line 518, in replace_all_validate\n",
" fgraph.replace(r, new_r, reason=reason, verbose=False)\n",
" File \"/Users/twiecki/miniconda3/envs/pymc3py38/lib/python3.8/site-packages/theano/gof/fg.py\", line 513, in replace\n",
" assert (node == 'output' and self.outputs[i] is r) or (node.inputs[i] is r)\n",
"AssertionError\n",
"\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"[2020-04-28 15:03:42] ERROR - prefect.TaskRunner | Unexpected error: AssertionError()\n",
"Traceback (most recent call last):\n",
" File \"/Users/twiecki/miniconda3/envs/pymc3py38/lib/python3.8/site-packages/prefect/engine/runner.py\", line 48, in inner\n",
" new_state = method(self, state, *args, **kwargs)\n",
" File \"/Users/twiecki/miniconda3/envs/pymc3py38/lib/python3.8/site-packages/prefect/engine/task_runner.py\", line 883, in get_task_run_state\n",
" result = timeout_handler(\n",
" File \"/Users/twiecki/miniconda3/envs/pymc3py38/lib/python3.8/site-packages/prefect/utilities/executors.py\", line 182, in timeout_handler\n",
" return fn(*args, **kwargs)\n",
" File \"<ipython-input-4-c604f0a61750>\", line 10, in infer_p\n",
" trace = pm.sample(tune=1500, target_accept=.9)\n",
" File \"/Users/twiecki/working/projects/pymc/pymc3/sampling.py\", line 498, in sample\n",
" trace = _mp_sample(**sample_args)\n",
" File \"/Users/twiecki/working/projects/pymc/pymc3/sampling.py\", line 1368, in _mp_sample\n",
" strace = _choose_backend(None, idx, model=model)\n",
" File \"/Users/twiecki/working/projects/pymc/pymc3/sampling.py\", line 1289, in _choose_backend\n",
" return NDArray(**kwds)\n",
" File \"/Users/twiecki/working/projects/pymc/pymc3/backends/ndarray.py\", line 197, in __init__\n",
" super().__init__(name, model, vars, test_point)\n",
" File \"/Users/twiecki/working/projects/pymc/pymc3/backends/base.py\", line 66, in __init__\n",
" self.fn = model.fastfn(vars)\n",
" File \"/Users/twiecki/working/projects/pymc/pymc3/model.py\", line 1129, in fastfn\n",
" f = self.makefn(outs, mode, *args, **kwargs)\n",
" File \"/Users/twiecki/working/projects/pymc/pymc3/model.py\", line 1095, in makefn\n",
" return theano.function(self.vars, outs,\n",
" File \"/Users/twiecki/miniconda3/envs/pymc3py38/lib/python3.8/site-packages/theano/compile/function.py\", line 306, in function\n",
" fn = pfunc(params=inputs,\n",
" File \"/Users/twiecki/miniconda3/envs/pymc3py38/lib/python3.8/site-packages/theano/compile/pfunc.py\", line 483, in pfunc\n",
" return orig_function(inputs, cloned_outputs, mode,\n",
" File \"/Users/twiecki/miniconda3/envs/pymc3py38/lib/python3.8/site-packages/theano/compile/function_module.py\", line 1832, in orig_function\n",
" m = Maker(inputs,\n",
" File \"/Users/twiecki/miniconda3/envs/pymc3py38/lib/python3.8/site-packages/theano/compile/function_module.py\", line 1519, in __init__\n",
" optimizer_profile = optimizer(fgraph)\n",
" File \"/Users/twiecki/miniconda3/envs/pymc3py38/lib/python3.8/site-packages/theano/gof/opt.py\", line 108, in __call__\n",
" return self.optimize(fgraph)\n",
" File \"/Users/twiecki/miniconda3/envs/pymc3py38/lib/python3.8/site-packages/theano/gof/opt.py\", line 97, in optimize\n",
" ret = self.apply(fgraph, *args, **kwargs)\n",
" File \"/Users/twiecki/miniconda3/envs/pymc3py38/lib/python3.8/site-packages/theano/gof/opt.py\", line 251, in apply\n",
" sub_prof = optimizer.optimize(fgraph)\n",
" File \"/Users/twiecki/miniconda3/envs/pymc3py38/lib/python3.8/site-packages/theano/gof/opt.py\", line 97, in optimize\n",
" ret = self.apply(fgraph, *args, **kwargs)\n",
" File \"/Users/twiecki/miniconda3/envs/pymc3py38/lib/python3.8/site-packages/theano/gof/opt.py\", line 2513, in apply\n",
" lopt_change = self.process_node(fgraph, node, lopt)\n",
" File \"/Users/twiecki/miniconda3/envs/pymc3py38/lib/python3.8/site-packages/theano/gof/opt.py\", line 2082, in process_node\n",
" self.failure_callback(e, self, repl_pairs, lopt, node)\n",
" File \"/Users/twiecki/miniconda3/envs/pymc3py38/lib/python3.8/site-packages/theano/gof/opt.py\", line 1933, in warn_inplace\n",
" return NavigatorOptimizer.warn(exc, nav, repl_pairs, local_opt, node)\n",
" File \"/Users/twiecki/miniconda3/envs/pymc3py38/lib/python3.8/site-packages/theano/gof/opt.py\", line 1919, in warn\n",
" raise exc\n",
" File \"/Users/twiecki/miniconda3/envs/pymc3py38/lib/python3.8/site-packages/theano/gof/opt.py\", line 2072, in process_node\n",
" fgraph.replace_all_validate_remove(repl_pairs,\n",
" File \"/Users/twiecki/miniconda3/envs/pymc3py38/lib/python3.8/site-packages/theano/gof/toolbox.py\", line 569, in replace_all_validate_remove\n",
" chk = fgraph.replace_all_validate(replacements, reason)\n",
" File \"/Users/twiecki/miniconda3/envs/pymc3py38/lib/python3.8/site-packages/theano/gof/toolbox.py\", line 518, in replace_all_validate\n",
" fgraph.replace(r, new_r, reason=reason, verbose=False)\n",
" File \"/Users/twiecki/miniconda3/envs/pymc3py38/lib/python3.8/site-packages/theano/gof/fg.py\", line 513, in replace\n",
" assert (node == 'output' and self.outputs[i] is r) or (node.inputs[i] is r)\n",
"AssertionError\n",
"[2020-04-28 15:03:42] INFO - prefect.TaskRunner | Task 'infer_p[0]': finished task run for task with final state: 'Failed'\n"
]
},
{
"data": {
"text/html": [
"\n",
" <div>\n",
" <style>\n",
" /* Turns off some styling */\n",
" progress {\n",
" /* gets rid of default border in Firefox and Opera. */\n",
" border: none;\n",
" /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
" background-size: auto;\n",
" }\n",
" .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
" background: #F44336;\n",
" }\n",
" </style>\n",
" <progress value='5000' class='' max='5000' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
" 100.00% [5000/5000 00:04<00:00 Sampling 2 chains, 0 divergences]\n",
" </div>\n",
" "
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"Sampling 2 chains for 1_500 tune and 1_000 draw iterations (3_000 + 2_000 draws total) took 12 seconds.\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"0.24389610741638615\n",
"[2020-04-28 15:03:53] INFO - prefect.TaskRunner | Task 'infer_p[1]': finished task run for task with final state: 'Success'\n",
"[2020-04-28 15:03:53] INFO - prefect.TaskRunner | Task 'infer_p': finished task run for task with final state: 'Mapped'\n",
"[2020-04-28 15:03:55] INFO - prefect.FlowRunner | Flow run FAILED: some reference tasks failed.\n"
]
}
],
"source": [
"# Map over two coins with DASK\n",
"with Flow('CoinFlow') as flow:\n",
" flips = flip_coin.map([.5, .25])\n",
" infer_p.map(flips)\n",
" flow.run(executor=DaskExecutor())"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[2020-04-28 14:13:53] INFO - prefect.FlowRunner | Beginning Flow run for 'CoinFlow'\n",
"[2020-04-28 14:13:53] INFO - prefect.FlowRunner | Starting flow run.\n",
"[2020-04-28 14:13:53] INFO - prefect.TaskRunner | Task 'flip_coin': Starting task run...\n",
"[2020-04-28 14:13:53] INFO - prefect.TaskRunner | Task 'flip_coin[1]': Starting task run...\n",
"[2020-04-28 14:13:53] INFO - prefect.TaskRunner | Task 'flip_coin[0]': Starting task run...\n",
"[2020-04-28 14:13:53] INFO - prefect.TaskRunner | Task 'flip_coin[1]': finished task run for task with final state: 'Success'\n",
"[2020-04-28 14:13:53] INFO - prefect.TaskRunner | Task 'flip_coin[0]': finished task run for task with final state: 'Success'\n",
"[2020-04-28 14:13:53] INFO - prefect.TaskRunner | Task 'flip_coin': finished task run for task with final state: 'Mapped'\n",
"[2020-04-28 14:13:53] INFO - prefect.TaskRunner | Task 'infer_p': Starting task run...\n",
"[2020-04-28 14:13:53] INFO - prefect.TaskRunner | Task 'infer_p[1]': Starting task run...\n",
"[2020-04-28 14:13:53] INFO - prefect.TaskRunner | Task 'infer_p[0]': Starting task run...\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"Auto-assigning NUTS sampler...\n",
"Initializing NUTS using jitter+adapt_diag...\n",
"Auto-assigning NUTS sampler...\n",
"Initializing NUTS using jitter+adapt_diag...\n",
"Initializing NUTS failed. Falling back to elementwise auto-assignment.\n",
"Multiprocess sampling (4 chains in 4 jobs)\n",
"NUTS: [bias]\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"[2020-04-28 14:13:54] ERROR - prefect.TaskRunner | Unexpected error: ValueError('Cannot compute test value: input 2 (Elemwise{Switch}.0) of Op Elemwise{Switch}(Elemwise{eq,no_inplace}.0, InplaceDimShuffle{}.0, Elemwise{Switch}.0) missing default value. ')\n",
"Traceback (most recent call last):\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gof/op.py\", line 1102, in get_debug_values\n",
" rval.append(get_test_value(arg))\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gof/op.py\", line 1007, in get_test_value\n",
" return PureOp._get_test_value(v_var)\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gof/op.py\", line 581, in _get_test_value\n",
" raise AttributeError('%s has no test value %s' % (v, detailed_err_msg))\n",
"AttributeError: Elemwise{Cast{float64}}.0 has no test value \n",
"Backtrace when that variable is created:\n",
"\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1326, in access_grad_cache\n",
" term = access_term_cache(node)[idx]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1021, in access_term_cache\n",
" output_grads = [access_grad_cache(var) for var in node.outputs]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1021, in <listcomp>\n",
" output_grads = [access_grad_cache(var) for var in node.outputs]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1326, in access_grad_cache\n",
" term = access_term_cache(node)[idx]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1021, in access_term_cache\n",
" output_grads = [access_grad_cache(var) for var in node.outputs]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1021, in <listcomp>\n",
" output_grads = [access_grad_cache(var) for var in node.outputs]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1326, in access_grad_cache\n",
" term = access_term_cache(node)[idx]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1161, in access_term_cache\n",
" input_grads = node.op.L_op(inputs, node.outputs,\n",
"\n",
"\n",
"During handling of the above exception, another exception occurred:\n",
"\n",
"Traceback (most recent call last):\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/pymc3/sampling.py\", line 442, in sample\n",
" start_, step = init_nuts(\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/pymc3/sampling.py\", line 2007, in init_nuts\n",
" step = pm.NUTS(potential=potential, model=model, **kwargs)\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/pymc3/step_methods/hmc/nuts.py\", line 162, in __init__\n",
" super().__init__(vars, **kwargs)\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/pymc3/step_methods/hmc/base_hmc.py\", line 86, in __init__\n",
" super().__init__(vars, blocked=blocked, model=model, dtype=dtype, **theano_kwargs)\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/pymc3/step_methods/arraystep.py\", line 243, in __init__\n",
" func = model.logp_dlogp_function(\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/pymc3/model.py\", line 895, in logp_dlogp_function\n",
" return ValueGradFunction(self.logpt, grad_vars, extra_vars, **kwargs)\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/pymc3/model.py\", line 625, in __init__\n",
" grad = tt.grad(self._cost_joined, self._vars_joined)\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 604, in grad\n",
" rval = _populate_grad_dict(var_to_app_to_idx,\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1371, in _populate_grad_dict\n",
" rval = [access_grad_cache(elem) for elem in wrt]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1371, in <listcomp>\n",
" rval = [access_grad_cache(elem) for elem in wrt]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1326, in access_grad_cache\n",
" term = access_term_cache(node)[idx]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1021, in access_term_cache\n",
" output_grads = [access_grad_cache(var) for var in node.outputs]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1021, in <listcomp>\n",
" output_grads = [access_grad_cache(var) for var in node.outputs]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1326, in access_grad_cache\n",
" term = access_term_cache(node)[idx]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1021, in access_term_cache\n",
" output_grads = [access_grad_cache(var) for var in node.outputs]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1021, in <listcomp>\n",
" output_grads = [access_grad_cache(var) for var in node.outputs]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1326, in access_grad_cache\n",
" term = access_term_cache(node)[idx]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1021, in access_term_cache\n",
" output_grads = [access_grad_cache(var) for var in node.outputs]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1021, in <listcomp>\n",
" output_grads = [access_grad_cache(var) for var in node.outputs]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1326, in access_grad_cache\n",
" term = access_term_cache(node)[idx]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1021, in access_term_cache\n",
" output_grads = [access_grad_cache(var) for var in node.outputs]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1021, in <listcomp>\n",
" output_grads = [access_grad_cache(var) for var in node.outputs]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1326, in access_grad_cache\n",
" term = access_term_cache(node)[idx]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1021, in access_term_cache\n",
" output_grads = [access_grad_cache(var) for var in node.outputs]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1021, in <listcomp>\n",
" output_grads = [access_grad_cache(var) for var in node.outputs]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1326, in access_grad_cache\n",
" term = access_term_cache(node)[idx]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1021, in access_term_cache\n",
" output_grads = [access_grad_cache(var) for var in node.outputs]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1021, in <listcomp>\n",
" output_grads = [access_grad_cache(var) for var in node.outputs]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1326, in access_grad_cache\n",
" term = access_term_cache(node)[idx]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1021, in access_term_cache\n",
" output_grads = [access_grad_cache(var) for var in node.outputs]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1021, in <listcomp>\n",
" output_grads = [access_grad_cache(var) for var in node.outputs]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1326, in access_grad_cache\n",
" term = access_term_cache(node)[idx]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1021, in access_term_cache\n",
" output_grads = [access_grad_cache(var) for var in node.outputs]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1021, in <listcomp>\n",
" output_grads = [access_grad_cache(var) for var in node.outputs]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1326, in access_grad_cache\n",
" term = access_term_cache(node)[idx]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1151, in access_term_cache\n",
" for orig_output_v, new_output_grad_v in get_debug_values(\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gof/op.py\", line 1108, in get_debug_values\n",
" missing_test_message(\"Argument \" + str(i) +\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gof/op.py\", line 1028, in missing_test_message\n",
" raise AttributeError(msg)\n",
"AttributeError: Argument 1 has no test value\n",
"\n",
"During handling of the above exception, another exception occurred:\n",
"\n",
"Traceback (most recent call last):\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gof/op.py\", line 625, in __call__\n",
" storage_map[ins] = [self._get_test_value(ins)]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gof/op.py\", line 581, in _get_test_value\n",
" raise AttributeError('%s has no test value %s' % (v, detailed_err_msg))\n",
"AttributeError: Elemwise{Switch}.0 has no test value \n",
"\n",
"During handling of the above exception, another exception occurred:\n",
"\n",
"Traceback (most recent call last):\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/prefect/engine/runner.py\", line 48, in inner\n",
" new_state = method(self, state, *args, **kwargs)\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/prefect/engine/task_runner.py\", line 883, in get_task_run_state\n",
" result = timeout_handler(\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/prefect/utilities/executors.py\", line 182, in timeout_handler\n",
" return fn(*args, **kwargs)\n",
" File \"<ipython-input-2-c604f0a61750>\", line 10, in infer_p\n",
" trace = pm.sample(tune=1500, target_accept=.9)\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/pymc3/sampling.py\", line 457, in sample\n",
" step = assign_step_methods(model, step, step_kwargs=kwargs)\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/pymc3/sampling.py\", line 208, in assign_step_methods\n",
" return instantiate_steppers(model, steps, selected_steps, step_kwargs)\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/pymc3/sampling.py\", line 129, in instantiate_steppers\n",
" step = step_class(vars=vars, **args)\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/pymc3/step_methods/hmc/nuts.py\", line 162, in __init__\n",
" super().__init__(vars, **kwargs)\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/pymc3/step_methods/hmc/base_hmc.py\", line 86, in __init__\n",
" super().__init__(vars, blocked=blocked, model=model, dtype=dtype, **theano_kwargs)\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/pymc3/step_methods/arraystep.py\", line 243, in __init__\n",
" func = model.logp_dlogp_function(\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/pymc3/model.py\", line 895, in logp_dlogp_function\n",
" return ValueGradFunction(self.logpt, grad_vars, extra_vars, **kwargs)\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/pymc3/model.py\", line 625, in __init__\n",
" grad = tt.grad(self._cost_joined, self._vars_joined)\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 604, in grad\n",
" rval = _populate_grad_dict(var_to_app_to_idx,\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1371, in _populate_grad_dict\n",
" rval = [access_grad_cache(elem) for elem in wrt]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1371, in <listcomp>\n",
" rval = [access_grad_cache(elem) for elem in wrt]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1326, in access_grad_cache\n",
" term = access_term_cache(node)[idx]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1021, in access_term_cache\n",
" output_grads = [access_grad_cache(var) for var in node.outputs]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1021, in <listcomp>\n",
" output_grads = [access_grad_cache(var) for var in node.outputs]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1326, in access_grad_cache\n",
" term = access_term_cache(node)[idx]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1021, in access_term_cache\n",
" output_grads = [access_grad_cache(var) for var in node.outputs]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1021, in <listcomp>\n",
" output_grads = [access_grad_cache(var) for var in node.outputs]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1326, in access_grad_cache\n",
" term = access_term_cache(node)[idx]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1021, in access_term_cache\n",
" output_grads = [access_grad_cache(var) for var in node.outputs]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1021, in <listcomp>\n",
" output_grads = [access_grad_cache(var) for var in node.outputs]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1326, in access_grad_cache\n",
" term = access_term_cache(node)[idx]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1021, in access_term_cache\n",
" output_grads = [access_grad_cache(var) for var in node.outputs]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1021, in <listcomp>\n",
" output_grads = [access_grad_cache(var) for var in node.outputs]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1326, in access_grad_cache\n",
" term = access_term_cache(node)[idx]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1021, in access_term_cache\n",
" output_grads = [access_grad_cache(var) for var in node.outputs]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1021, in <listcomp>\n",
" output_grads = [access_grad_cache(var) for var in node.outputs]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1326, in access_grad_cache\n",
" term = access_term_cache(node)[idx]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1021, in access_term_cache\n",
" output_grads = [access_grad_cache(var) for var in node.outputs]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1021, in <listcomp>\n",
" output_grads = [access_grad_cache(var) for var in node.outputs]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1326, in access_grad_cache\n",
" term = access_term_cache(node)[idx]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1021, in access_term_cache\n",
" output_grads = [access_grad_cache(var) for var in node.outputs]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1021, in <listcomp>\n",
" output_grads = [access_grad_cache(var) for var in node.outputs]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1326, in access_grad_cache\n",
" term = access_term_cache(node)[idx]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1021, in access_term_cache\n",
" output_grads = [access_grad_cache(var) for var in node.outputs]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1021, in <listcomp>\n",
" output_grads = [access_grad_cache(var) for var in node.outputs]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1326, in access_grad_cache\n",
" term = access_term_cache(node)[idx]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1021, in access_term_cache\n",
" output_grads = [access_grad_cache(var) for var in node.outputs]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1021, in <listcomp>\n",
" output_grads = [access_grad_cache(var) for var in node.outputs]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1326, in access_grad_cache\n",
" term = access_term_cache(node)[idx]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1021, in access_term_cache\n",
" output_grads = [access_grad_cache(var) for var in node.outputs]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1021, in <listcomp>\n",
" output_grads = [access_grad_cache(var) for var in node.outputs]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1326, in access_grad_cache\n",
" term = access_term_cache(node)[idx]\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gradient.py\", line 1161, in access_term_cache\n",
" input_grads = node.op.L_op(inputs, node.outputs,\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/tensor/elemwise.py\", line 543, in L_op\n",
" rval = self._bgrad(inputs, outs, ograds)\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/tensor/elemwise.py\", line 643, in _bgrad\n",
" ret.append(transform(scalar_igrad))\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/tensor/elemwise.py\", line 634, in transform\n",
" new_r = Elemwise(node.op, {})(\n",
" File \"/Users/systrom/miniconda3/envs/prefect/lib/python3.8/site-packages/theano/gof/op.py\", line 637, in __call__\n",
" raise ValueError(\n",
"ValueError: Cannot compute test value: input 2 (Elemwise{Switch}.0) of Op Elemwise{Switch}(Elemwise{eq,no_inplace}.0, InplaceDimShuffle{}.0, Elemwise{Switch}.0) missing default value. \n",
"[2020-04-28 14:13:55] INFO - prefect.TaskRunner | Task 'infer_p[0]': finished task run for task with final state: 'Failed'\n"
]
}
],
"source": [
"# Map over two coins with DASK\n",
"with Flow('CoinFlow') as flow:\n",
" flips = flip_coin.map([.5, .25])\n",
" infer_p.map(flips)\n",
" flow.run(executor=LocalDaskExecutor(scheduler='threads'))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "pymc3",
"language": "python",
"name": "pymc3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.6"
}
},
"nbformat": 4,
"nbformat_minor": 4
}
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