TypeError: Expected bool for argument 'transpose

TypeError: Expected bool for argument 'transpose_a' not <tensorflow.python.ops.variables.Variable object at 0x7f0732493630>.
とエラーが出ました。

def xxx(train_X, train_y, test_X):
    train_X= tf.placeholder(tf.float32,[None,784])
    train_y= tf.placeholder(tf.float32,[None,784])
    W = tf.Variable(tf.zeros([784,10]))
    b = tf.Variable(tf.zeros([10]))
    y = tf.nn.softmax(tf.matmul(train_X, train_y,W)+b)
    pred_y= tf.placeholder(tf.float32,[None,10])
    cross_entropy = -tf.reduce_sum(pred_y*tf.log(y))
    train_step = tf.train.GradientDescentOptimizer(0.01).minimize(cross_entropy)
    init = tf.initialize_all_variables()
    correct_prediction = tf.equal(tf.argmax(y,1), tf.argmax(y_,1))
    accuracy = tf.reduce_mean(tf.cast(correct_prediction,"foat"))
    return pred_y

とMNISTを読み込んで推測する準備をするコードを記事を参考にしながら書きました。
訓練画像を入れる変数→重みの用意→バイアスの用意→ソフトマックス回帰→予想ラベルの用意→交差エントロピー→勾配硬化法→変数の初期化→正しいかの予測→精度の計算の順にコードを構築しました。
さらに、このxxxメソッドを呼び出すコードを以下に書きました。

from sklearn.utils import shuffle
from sklearn.metrics import f1_score
from sklearn.datasets import fetch_mldata
from sklearn.model_selection import train_test_split

import numpy as np
import tensorflow as tf

del [
    tf.app,
    tf.compat,
    tf.contrib,
    tf.errors,
    tf.gfile,
    tf.graph_util,
    tf.image,
    tf.layers,
    tf.logging,
    tf.losses,
    tf.metrics,
    tf.python_io,
    tf.resource_loader,
    tf.saved_model,
    tf.sdca,
    tf.sets,
    tf.summary,
    tf.sysconfig,
    tf.test,
    tf.train
]

def load_mnist():
    mnist = fetch_mldata('MNIST original')
    mnist_X, mnist_y = shuffle(mnist.data.astype('float32'),
                               mnist.target.astype('int32'), random_state=42)

    mnist_X = mnist_X / 255.0

    return train_test_split(mnist_X, mnist_y,
                test_size=0.2,
                random_state=42)

def validate():
    train_X, test_X, train_y, test_y = load_mnist()

    # validate for small dataset
    train_X_mini = train_X[:100]
    train_y_mini = train_y[:100]
    test_X_mini = test_X[:100]
    test_y_mini = test_y[:100]

    pred_y = xxx(train_X_mini, train_y_mini, test_X_mini)
    print(f1_score(test_y_mini, pred_y, average='macro'))

def score():
    train_X, test_X, train_y, test_y = load_mnist()
    pred_y = xxx(train_X, train_y, test_X)
    print(f1_score(test_y, pred_y, average='macro'))

validate()
#score()

これらの３つのコードを上から順に Jupyter Notebookで実行したのですが、

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-13-6eaef2a4f45a> in <module>()
----> 1 validate()
      2 #score()

<ipython-input-12-64b812fb44e9> in validate_homework()
     50     test_y_mini = test_y[:100]
     51 
---> 52     pred_y = xxx(train_X_mini, train_y_mini, test_X_mini)
     53     print(f1_score(test_y_mini, pred_y, average='macro'))
     54 

<ipython-input-11-f4e0642d25c8> in homework(train_X, train_y, test_X)
      4     W = tf.Variable(tf.zeros([784,10]))
      5     b = tf.Variable(tf.zeros([10]))
----> 6     y = tf.nn.softmax(tf.matmul(train_X, train_y,W)+b)
      7     #1行10列のベクトルに正解ラベルがなるようにしている？
      8     pred_y= tf.placeholder(tf.float32,[None,10])

/usr/local/lib/python3.4/dist-packages/tensorflow/python/ops/math_ops.py in matmul(a, b, transpose_a, transpose_b, adjoint_a, adjoint_b, a_is_sparse, b_is_sparse, name)
   1853     else:
   1854       return gen_math_ops._mat_mul(
-> 1855           a, b, transpose_a=transpose_a, transpose_b=transpose_b, name=name)
   1856 
   1857 

/usr/local/lib/python3.4/dist-packages/tensorflow/python/ops/gen_math_ops.py in _mat_mul(a, b, transpose_a, transpose_b, name)
   1452   """
   1453   result = _op_def_lib.apply_op("MatMul", a=a, b=b, transpose_a=transpose_a,
-> 1454                                 transpose_b=transpose_b, name=name)
   1455   return result
   1456 

/usr/local/lib/python3.4/dist-packages/tensorflow/python/framework/op_def_library.py in apply_op(self, op_type_name, name, **keywords)
    690           attr_value.list.f.extend([_MakeFloat(x, key) for x in value])
    691         elif attr_def.type == "bool":
--> 692           attr_value.b = _MakeBool(value, key)
    693         elif attr_def.type == "list(bool)":
    694           attr_value.list.b.extend([_MakeBool(x, key) for x in value])

/usr/local/lib/python3.4/dist-packages/tensorflow/python/framework/op_def_library.py in _MakeBool(v, arg_name)
    167   if not isinstance(v, bool):
    168     raise TypeError("Expected bool for argument '%s' not %s." %
--> 169                     (arg_name, repr(v)))
    170   return v
    171 

TypeError: Expected bool for argument 'transpose_a' not <tensorflow.python.ops.variables.Variable object at 0x7f0732493630>.

とエラーが出ました。私が書いていない'transpose_a'のところでエラーが出ているのが理解できません。どう直せばよいのでしょうか？