linear_regression.py

linear_regression.py

import tensorflow as tf

W = tf.Variable(tf.zeros([2, 1]), name="weights")
b = tf.Variable(0., name="bias")

def inference(X):
    return tf.matmul(X, W) + b

def loss(X,Y):
    Y_predicted = inference(X)
    return tf.reduce_sum(tf.squared_difference(Y, Y_predicted))

def inputs():
    weight_age = [[84, 46], [73, 20], [65, 52], [70, 30], [76, 57], [69, 25], [63, 28], [72, 36], [79, 57], [75, 44], [27, 24], [89, 31], [65, 52], [57, 23], [59, 60], [69, 48], [60, 34], [79, 51], [75, 50], [82, 34], [59, 46], [67, 23], [85, 37], [55, 40], [63, 30]]
    blood_fat_content = [354, 190, 405, 263, 451, 302, 288, 385, 402, 365, 209, 290, 346, 254, 395, 434, 220, 374, 308, 220, 311, 181, 274, 303, 244]
    return tf.to_float(weight_age), tf.to_float(blood_fat_content)

def train(total_loss):
    learning_rate = 0.00000001
    return tf.train.GradientDescentOptimizer(learning_rate).minimize(total_loss)

def evaluates(sess, X, Y):
    print(sess.run(inference([80. ,25.])))
    print(sess.run(inference([65. ,25.])))

with tf.Session() as sess:
    tf.global_variables_initializer().run()
    X, Y = inputs()
    print("X Rank: ",tf.rank(X))
    print("Y Rank: ",tf.rank(Y))
    total_loss = loss(X, Y)
    train_op = train(total_loss)
    coord = tf.train.Coordinator()
    threads = tf.train.start_queue_runners(sess=sess, coord=coord)

    training_steps = 1000
    for step in range(training_steps):
        sess.run([train_op])
        if step%10 == 0:
            print("loss: ", sess.run([total_loss]))

    evaluates(sess, X, Y)

    coord.request_stop()
    coord.join(threads)
    sess.close()
    
    # Output 
    '''
    loss:  [5343514.5]
loss:  [5343446.5]
loss:  [5343380.0]
loss:  [5343314.5]
loss:  [5343250.0]
loss:  [5343187.5]
loss:  [5343128.0]
loss:  [5343067.5]
loss:  [5343010.5]
loss:  [5342952.5]
loss:  [5342897.5]
loss:  [5342843.0]
loss:  [5342791.5]
loss:  [5342738.5]
loss:  [5342688.5]
loss:  [5342638.5]
loss:  [5342589.5]
loss:  [5342543.0]
loss:  [5342496.5]
loss:  [5342449.5]
loss:  [5342406.0]
loss:  [5342363.0]
loss:  [5342319.5]
loss:  [5342277.5]
loss:  [5342236.0]
loss:  [5342197.5]
loss:  [5342157.0]
loss:  [5342118.5]
loss:  [5342080.5]
loss:  [5342043.0]
loss:  [5342007.5]
Traceback (most recent call last):
  File "/Users/shivammishra/miniconda3/envs/tensorflow/lib/python3.6/site-packages/tensorflow/python/framework/common_shapes.py", line 671, in _call_cpp_shape_fn_impl
    input_tensors_as_shapes, status)
  File "/Users/shivammishra/miniconda3/envs/tensorflow/lib/python3.6/contextlib.py", line 88, in __exit__
    next(self.gen)
  File "/Users/shivammishra/miniconda3/envs/tensorflow/lib/python3.6/site-packages/tensorflow/python/framework/errors_impl.py", line 466, in raise_exception_on_not_ok_status
    pywrap_tensorflow.TF_GetCode(status))
tensorflow.python.framework.errors_impl.InvalidArgumentError: Shape must be rank 2 but is rank 1 for 'MatMul_1' (op: 'MatMul') with input shapes: [2], [2,1].

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "linear_regression.py", line 42, in <module>
    evaluates(sess, X, Y)
  File "linear_regression.py", line 23, in evaluates
    print(sess.run(inference([80. ,25.])))
  File "linear_regression.py", line 7, in inference
    return tf.matmul(X, W) + b
  File "/Users/shivammishra/miniconda3/envs/tensorflow/lib/python3.6/site-packages/tensorflow/python/ops/math_ops.py", line 1801, in matmul
    a, b, transpose_a=transpose_a, transpose_b=transpose_b, name=name)
  File "/Users/shivammishra/miniconda3/envs/tensorflow/lib/python3.6/site-packages/tensorflow/python/ops/gen_math_ops.py", line 1263, in _mat_mul
    transpose_b=transpose_b, name=name)
  File "/Users/shivammishra/miniconda3/envs/tensorflow/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py", line 768, in apply_op
    op_def=op_def)
  File "/Users/shivammishra/miniconda3/envs/tensorflow/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 2338, in create_op
    set_shapes_for_outputs(ret)
  File "/Users/shivammishra/miniconda3/envs/tensorflow/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 1719, in set_shapes_for_outputs
    shapes = shape_func(op)
  File "/Users/shivammishra/miniconda3/envs/tensorflow/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 1669, in call_with_requiring
    return call_cpp_shape_fn(op, require_shape_fn=True)
  File "/Users/shivammishra/miniconda3/envs/tensorflow/lib/python3.6/site-packages/tensorflow/python/framework/common_shapes.py", line 610, in call_cpp_shape_fn
    debug_python_shape_fn, require_shape_fn)
  File "/Users/shivammishra/miniconda3/envs/tensorflow/lib/python3.6/site-packages/tensorflow/python/framework/common_shapes.py", line 676, in _call_cpp_shape_fn_impl
    raise ValueError(err.message)
ValueError: Shape must be rank 2 but is rank 1 for 'MatMul_1' (op: 'MatMul') with input shapes: [2], [2,1].
    '''