提交 a219fdb0 编写于 作者: A A. Unique TensorFlower 提交者: TensorFlower Gardener

Update generated Python Op docs.

Change: 125400645
上级 4093a847
...@@ -2403,9 +2403,9 @@ estimator = LinearClassifier( ...@@ -2403,9 +2403,9 @@ estimator = LinearClassifier(
)) ))
# Input builders # Input builders
def input_fn_train: # returns x, y, where y is a tensor of dimension 1 def input_fn_train: # returns x, y
... ...
def input_fn_eval: # returns x, y, where y is a tensor of dimension 1 def input_fn_eval: # returns x, y
... ...
estimator.fit(input_fn=input_fn_train) estimator.fit(input_fn=input_fn_train)
estimator.evaluate(input_fn=input_fn_eval) estimator.evaluate(input_fn=input_fn_eval)
...@@ -2767,9 +2767,9 @@ estimator = LinearRegressor( ...@@ -2767,9 +2767,9 @@ estimator = LinearRegressor(
feature_columns=[occupation, education_x_occupation]) feature_columns=[occupation, education_x_occupation])
# Input builders # Input builders
def input_fn_train: # returns x, y, where y is a tensor of dimension 1 def input_fn_train: # returns x, y
... ...
def input_fn_eval: # returns x, y, where y is a tensor of dimension 1 def input_fn_eval: # returns x, y
... ...
estimator.fit(input_fn=input_fn_train) estimator.fit(input_fn=input_fn_train)
estimator.evaluate(input_fn=input_fn_eval) estimator.evaluate(input_fn=input_fn_eval)
......
...@@ -18,9 +18,9 @@ estimator = LinearRegressor( ...@@ -18,9 +18,9 @@ estimator = LinearRegressor(
feature_columns=[occupation, education_x_occupation]) feature_columns=[occupation, education_x_occupation])
# Input builders # Input builders
def input_fn_train: # returns x, y, where y is a tensor of dimension 1 def input_fn_train: # returns x, y
... ...
def input_fn_eval: # returns x, y, where y is a tensor of dimension 1 def input_fn_eval: # returns x, y
... ...
estimator.fit(input_fn=input_fn_train) estimator.fit(input_fn=input_fn_train)
estimator.evaluate(input_fn=input_fn_eval) estimator.evaluate(input_fn=input_fn_eval)
......
...@@ -35,9 +35,9 @@ estimator = LinearClassifier( ...@@ -35,9 +35,9 @@ estimator = LinearClassifier(
)) ))
# Input builders # Input builders
def input_fn_train: # returns x, y, where y is a tensor of dimension 1 def input_fn_train: # returns x, y
... ...
def input_fn_eval: # returns x, y, where y is a tensor of dimension 1 def input_fn_eval: # returns x, y
... ...
estimator.fit(input_fn=input_fn_train) estimator.fit(input_fn=input_fn_train)
estimator.evaluate(input_fn=input_fn_eval) estimator.evaluate(input_fn=input_fn_eval)
......
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