import pymc3 as pm import numpy as np x = np.linspace(0,1,100) y_true = 3*x + 5 y_obs = y_true + np.random.normal(loc=0, scale=0.02,size=100) with pm.Model() as model: a = pm.Normal(‘a’, mu=2.0, sigma=3.0) b = pm.Normal(‘b’, mu=2.0, sigma=3.0) y_model = a*x + b s = pm.HalfNormal(‘s’, sigma=0.05) likelihood = pm.Normal(‘y’, mu=y_model, sigma=s, observed = y_obs) trace = ..

#### Category : theano

I am trying to convert a Pandas DataFrame into a shared tensor variable in Theano, with the following code: vis_first = theano.shared(np.asarray(df_first), ‘vis_first’) The type of this vis_first variable, is theano.compile.sharedvalue.SharedVariable. Why does this happen and how can I make the variable into a theano.tensor.sharedvar.TensorSharedVariable variable instead? Source: Python..

I’m new to Theano, however, I’m trying to teach myself the ropes of it as it is still the backend of PyMC3 until the switch to Jax is further along. The official(?) tutorial gives the following instructions: import theano from theano import tensor a = tensor.dscalar() b = tensor.dscalar() c = a + b f ..

I am trying to extend the ideas of item response theory to multiple responses. Consider a marketing survey, which asks customers, "what’s the deciding factor in whether or not you purchase product X?" Where answers are {0: price, 1: durability, 2: ease-of-use}. Here is some synthetic data (rows are customers, columns are products, each cell ..

I have model in pymc2 like this. p = Uniform(name=’p’, lower=p_lowers, upper=p_uppers, value=p_values) MIM_Model = pm.Deterministic(eval = MIM_eval, name = ‘NEE_Model’, parents = {‘p’: p, ‘Csom_0’: Csom_0, ‘Tave’: Tave, ‘Tmax’: Tmax, ‘Rg’: Rg, ‘RH’: RH, ‘VPD’:VPD,’Lat’:Lat,’a2′: a2}, doc = ‘model construction’, trace = True, verbose = 0, dtype = float, plot = False, cache_depth = ..

my models are trained using tensorflow in google colab. I want to load them in a django server with keras using theano as backend.Here is my error when i triy to load that model. 2020-09-18 05:00:57,559: File "/home/anush123/sample/transfer/views.py", line 27, in <module> 2020-09-18 05:00:57,559: models[‘1’] = load_model("/home/anush123/sample/static/car_model.h5",compile=False) 2020-09-18 05:00:57,559: 2020-09-18 05:00:57,559: File "/home/anush123/.virtualenvs/myenv/lib/python3.7/site-packages/keras/engine/saving.py", line 419, ..

I am trying to import theano, but it directly import GPU. I want to import theono on CPU. here is the error when i try to import theano ————————————————————————————————– ~Anaconda3libsite-packageslasagnelayersdnn.py in <module>() 1 import theano —-> 2 from theano.sandbox.cuda import dnn 3 4 from .. import init 5 from .. import nonlinearities ~Anaconda3libsite-packagestheanosandboxcuda__init__.py in <module>() ..

I am trying to set up theano backend for keras in my django server. And i got this error. I have no idea about this error please help me. (func.__name__, getattr(func, api_names_attr))) # pylint: disable here is link for full error i got in my server error log. I am using pythonanywhere hosting. Source: Python ..

I’m training on pymc3 so I builded 2d clusterization model: generated data (image) I have debugged my model and here is the code: import numpy as np from scipy import stats import matplotlib.pyplot as plt import pymc3 as pm import theano import theano.tensor as tt #Generating data N = 1000 p = (0.1, 0.3, 0.6) ..

I am working on a bayesian model using pymc3. I have a data set with 29 rows and three columns: "K", "B", "M". Where "B" and "M" are predictor variables. column B has a few missing values. I have built the following model, which usages pm.MvNormal distribution to support the imputation of missing values. Model ..

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