l3lab/ntp-mathlib huggingface dataset:
@[to_additive]
theorem MonoidHomClass.isometry_iff_norm [MonoidHomClass 𝓕 E F] (f : 𝓕) :
    Isometry f ↔ ∀ x, ‖f x‖ = ‖x‖ := by
  simp only [isometry_iff_dist_eq, dist_eq_norm_div, ← map_div]
  

Proof state:
𝓕 : Type u_1
𝕜 : Type u_2
α : Type u_3
ι : Type u_4
κ : Type u_5
E : Type u_6
F : Type u_7
G : Type u_8
inst✝³ : SeminormedGroup E
inst✝² : SeminormedGroup F
inst✝¹ : SeminormedGroup G
s : Set E
a a₁ a₂ b b₁ b₂ : E
r r₁ r₂ : ℝ
inst✝ : MonoidHomClass 𝓕 E F
f : 𝓕
⊢ (∀ (x y : E), ‖f (x / y)‖ = ‖x / y‖) ↔ ∀ (x : E), ‖f x‖ = ‖x‖

Next tactic:
refine' ⟨fun h x => _, fun h x y => h _⟩
@[to_additive]
theorem MonoidHomClass.isometry_iff_norm [MonoidHomClass 𝓕 E F] (f : 𝓕) :
    Isometry f ↔ ∀ x, ‖f x‖ = ‖x‖ := by
  simp only [isometry_iff_dist_eq, dist_eq_norm_div, ← map_div]
  refine' ⟨fun h x => _, fun h x y => h _⟩
  

Proof state:
𝓕 : Type u_1
𝕜 : Type u_2
α : Type u_3
ι : Type u_4
κ : Type u_5
E : Type u_6
F : Type u_7
G : Type u_8
inst✝³ : SeminormedGroup E
inst✝² : SeminormedGroup F
inst✝¹ : SeminormedGroup G
s : Set E
a a₁ a₂ b b₁ b₂ : E
r r₁ r₂ : ℝ
inst✝ : MonoidHomClass 𝓕 E F
f : 𝓕
h : ∀ (x y : E), ‖f (x / y)‖ = ‖x / y‖
x : E
⊢ ‖f x‖ = ‖x‖

Next tactic:
simpa using h x 1
@[to_additive]
theorem ne_one_of_nnnorm_ne_zero {a : E} : ‖a‖₊ ≠ 0 → a ≠ 1 :=
  mt <| by
    

Proof state:
𝓕 : Type u_1
𝕜 : Type u_2
α : Type u_3
ι : Type u_4
κ : Type u_5
E : Type u_6
F : Type u_7
G : Type u_8
inst✝² : SeminormedGroup E
inst✝¹ : SeminormedGroup F
inst✝ : SeminormedGroup G
s : Set E
a✝ a₁ a₂ b b₁ b₂ : E
r r₁ r₂ : ℝ
a : E
⊢ a = 1 → ‖a‖₊ = 0

Next tactic:
rintro rfl
@[to_additive]
theorem ne_one_of_nnnorm_ne_zero {a : E} : ‖a‖₊ ≠ 0 → a ≠ 1 :=
  mt <| by
    rintro rfl
    

Proof state:
𝓕 : Type u_1
𝕜 : Type u_2
α : Type u_3
ι : Type u_4
κ : Type u_5
E : Type u_6
F : Type u_7
G : Type u_8
inst✝² : SeminormedGroup E
inst✝¹ : SeminormedGroup F
inst✝ : SeminormedGroup G
s : Set E
a a₁ a₂ b b₁ b₂ : E
r r₁ r₂ : ℝ
⊢ ‖1‖₊ = 0

Next tactic:
exact nnnorm_one'
@[to_additive]
theorem edist_eq_coe_nnnorm_div (a b : E) : edist a b = ‖a / b‖₊ := by
  

Proof state:
𝓕 : Type u_1
𝕜 : Type u_2
α : Type u_3
ι : Type u_4
κ : Type u_5
E : Type u_6
F : Type u_7
G : Type u_8
inst✝² : SeminormedGroup E
inst✝¹ : SeminormedGroup F
inst✝ : SeminormedGroup G
s : Set E
a✝ a₁ a₂ b✝ b₁ b₂ : E
r r₁ r₂ : ℝ
a b : E
⊢ edist a b = ↑‖a / b‖₊

Next tactic:
rw [edist_dist, dist_eq_norm_div, ofReal_norm_eq_coe_nnnorm']
@[to_additive edist_eq_coe_nnnorm]
theorem edist_eq_coe_nnnorm' (x : E) : edist x 1 = (‖x‖₊ : ℝ≥0∞) := by
  

Proof state:
𝓕 : Type u_1
𝕜 : Type u_2
α : Type u_3
ι : Type u_4
κ : Type u_5
E : Type u_6
F : Type u_7
G : Type u_8
inst✝² : SeminormedGroup E
inst✝¹ : SeminormedGroup F
inst✝ : SeminormedGroup G
s : Set E
a a₁ a₂ b b₁ b₂ : E
r r₁ r₂ : ℝ
x : E
⊢ edist x 1 = ↑‖x‖₊

Next tactic:
rw [edist_eq_coe_nnnorm_div, div_one]
@[to_additive]
theorem edist_mulIndicator (s t : Set α) (f : α → E) (x : α) :
    edist (s.mulIndicator f x) (t.mulIndicator f x) = ‖(s ∆ t).mulIndicator f x‖₊ := by
  

Proof state:
𝓕 : Type u_1
𝕜 : Type u_2
α : Type u_3
ι : Type u_4
κ : Type u_5
E : Type u_6
F : Type u_7
G : Type u_8
inst✝² : SeminormedGroup E
inst✝¹ : SeminormedGroup F
inst✝ : SeminormedGroup G
s✝ : Set E
a a₁ a₂ b b₁ b₂ : E
r r₁ r₂ : ℝ
s t : Set α
f : α → E
x : α
⊢ edist (Set.mulIndicator s f x) (Set.mulIndicator t f x) = ↑‖Set.mulIndicator (s ∆ t) f x‖₊

Next tactic:
rw [edist_nndist, nndist_mulIndicator]
@[to_additive]
theorem mem_emetric_ball_one_iff {r : ℝ≥0∞} : a ∈ EMetric.ball (1 : E) r ↔ ↑‖a‖₊ < r := by
  

Proof state:
𝓕 : Type u_1
𝕜 : Type u_2
α : Type u_3
ι : Type u_4
κ : Type u_5
E : Type u_6
F : Type u_7
G : Type u_8
inst✝² : SeminormedGroup E
inst✝¹ : SeminormedGroup F
inst✝ : SeminormedGroup G
s : Set E
a a₁ a₂ b b₁ b₂ : E
r✝ r₁ r₂ : ℝ
r : ℝ≥0∞
⊢ a ∈ EMetric.ball 1 r ↔ ↑‖a‖₊ < r

Next tactic:
rw [EMetric.mem_ball, edist_eq_coe_nnnorm']
@[to_additive]
theorem MonoidHomClass.antilipschitz_of_bound [MonoidHomClass 𝓕 E F] (f : 𝓕) {K : ℝ≥0}
    (h : ∀ x, ‖x‖ ≤ K * ‖f x‖) : AntilipschitzWith K f :=
  AntilipschitzWith.of_le_mul_dist fun x y => by
    

Proof state:
𝓕 : Type u_1
𝕜 : Type u_2
α : Type u_3
ι : Type u_4
κ : Type u_5
E : Type u_6
F : Type u_7
G : Type u_8
inst✝³ : SeminormedGroup E
inst✝² : SeminormedGroup F
inst✝¹ : SeminormedGroup G
s : Set E
a a₁ a₂ b b₁ b₂ : E
r r₁ r₂ : ℝ
inst✝ : MonoidHomClass 𝓕 E F
f : 𝓕
K : ℝ≥0
h : ∀ (x : E), ‖x‖ ≤ ↑K * ‖f x‖
x y : E
⊢ dist x y ≤ ↑K * dist (f x) (f y)

Next tactic:
simpa only [dist_eq_norm_div, map_div] using h (x / y)
@[to_additive LipschitzWith.norm_le_mul]
theorem LipschitzWith.norm_le_mul' {f : E → F} {K : ℝ≥0} (h : LipschitzWith K f) (hf : f 1 = 1)
    (x) : ‖f x‖ ≤ K * ‖x‖ := by 

Proof state:
𝓕 : Type u_1
𝕜 : Type u_2
α : Type u_3
ι : Type u_4
κ : Type u_5
E : Type u_6
F : Type u_7
G : Type u_8
inst✝² : SeminormedGroup E
inst✝¹ : SeminormedGroup F
inst✝ : SeminormedGroup G
s : Set E
a a₁ a₂ b b₁ b₂ : E
r r₁ r₂ : ℝ
f : E → F
K : ℝ≥0
h : LipschitzWith K f
hf : f 1 = 1
x : E
⊢ ‖f x‖ ≤ ↑K * ‖x‖

Next tactic:
simpa only [dist_one_right, hf] using h.dist_le_mul x 1
@[to_additive AntilipschitzWith.le_mul_norm]
theorem AntilipschitzWith.le_mul_norm' {f : E → F} {K : ℝ≥0} (h : AntilipschitzWith K f)
    (hf : f 1 = 1) (x) : ‖x‖ ≤ K * ‖f x‖ := by
  

Proof state:
𝓕 : Type u_1
𝕜 : Type u_2
α : Type u_3
ι : Type u_4
κ : Type u_5
E : Type u_6
F : Type u_7
G : Type u_8
inst✝² : SeminormedGroup E
inst✝¹ : SeminormedGroup F
inst✝ : SeminormedGroup G
s : Set E
a a₁ a₂ b b₁ b₂ : E
r r₁ r₂ : ℝ
f : E → F
K : ℝ≥0
h : AntilipschitzWith K f
hf : f 1 = 1
x : E
⊢ ‖x‖ ≤ ↑K * ‖f x‖

Next tactic:
simpa only [dist_one_right, hf] using h.le_mul_dist x 1
@[to_additive]
theorem tendsto_iff_norm_div_tendsto_zero {f : α → E} {a : Filter α} {b : E} :
    Tendsto f a (𝓝 b) ↔ Tendsto (fun e => ‖f e / b‖) a (𝓝 0) := by
  

Proof state:
𝓕 : Type u_1
𝕜 : Type u_2
α : Type u_3
ι : Type u_4
κ : Type u_5
E : Type u_6
F : Type u_7
G : Type u_8
inst✝² : SeminormedGroup E
inst✝¹ : SeminormedGroup F
inst✝ : SeminormedGroup G
s : Set E
a✝ a₁ a₂ b✝ b₁ b₂ : E
r r₁ r₂ : ℝ
f : α → E
a : Filter α
b : E
⊢ Tendsto f a (𝓝 b) ↔ Tendsto (fun e => ‖f e / b‖) a (𝓝 0)

Next tactic:
simp only [← dist_eq_norm_div, ← tendsto_iff_dist_tendsto_zero]
@[to_additive]
theorem tendsto_one_iff_norm_tendsto_zero {f : α → E} {a : Filter α} :
    Tendsto f a (𝓝 1) ↔ Tendsto (‖f ·‖) a (𝓝 0) :=
  tendsto_iff_norm_div_tendsto_zero.trans <| by 

Proof state:
𝓕 : Type u_1
𝕜 : Type u_2
α : Type u_3
ι : Type u_4
κ : Type u_5
E : Type u_6
F : Type u_7
G : Type u_8
inst✝² : SeminormedGroup E
inst✝¹ : SeminormedGroup F
inst✝ : SeminormedGroup G
s : Set E
a✝ a₁ a₂ b b₁ b₂ : E
r r₁ r₂ : ℝ
f : α → E
a : Filter α
⊢ Tendsto (fun e => ‖f e / 1‖) a (𝓝 0) ↔ Tendsto (fun x => ‖f x‖) a (𝓝 0)

Next tactic:
simp only [div_one]
@[to_additive]
theorem comap_norm_nhds_one : comap norm (𝓝 0) = 𝓝 (1 : E) := by
  

Proof state:
𝓕 : Type u_1
𝕜 : Type u_2
α : Type u_3
ι : Type u_4
κ : Type u_5
E : Type u_6
F : Type u_7
G : Type u_8
inst✝² : SeminormedGroup E
inst✝¹ : SeminormedGroup F
inst✝ : SeminormedGroup G
s : Set E
a a₁ a₂ b b₁ b₂ : E
r r₁ r₂ : ℝ
⊢ comap norm (𝓝 0) = 𝓝 1

Next tactic:
simpa only [dist_one_right] using nhds_comap_dist (1 : E)
@[to_additive]
theorem tendsto_norm_div_self (x : E) : Tendsto (fun a => ‖a / x‖) (𝓝 x) (𝓝 0) := by
  

Proof state:
𝓕 : Type u_1
𝕜 : Type u_2
α : Type u_3
ι : Type u_4
κ : Type u_5
E : Type u_6
F : Type u_7
G : Type u_8
inst✝² : SeminormedGroup E
inst✝¹ : SeminormedGroup F
inst✝ : SeminormedGroup G
s : Set E
a a₁ a₂ b b₁ b₂ : E
r r₁ r₂ : ℝ
x : E
⊢ Tendsto (fun a => ‖a / x‖) (𝓝 x) (𝓝 0)

Next tactic:
simpa [dist_eq_norm_div] using
    tendsto_id.dist (tendsto_const_nhds : Tendsto (fun _a => (x : E)) (𝓝 x) _)
@[to_additive tendsto_norm]
theorem tendsto_norm' {x : E} : Tendsto (fun a => ‖a‖) (𝓝 x) (𝓝 ‖x‖) := by
  

Proof state:
𝓕 : Type u_1
𝕜 : Type u_2
α : Type u_3
ι : Type u_4
κ : Type u_5
E : Type u_6
F : Type u_7
G : Type u_8
inst✝² : SeminormedGroup E
inst✝¹ : SeminormedGroup F
inst✝ : SeminormedGroup G
s : Set E
a a₁ a₂ b b₁ b₂ : E
r r₁ r₂ : ℝ
x : E
⊢ Tendsto (fun a => ‖a‖) (𝓝 x) (𝓝 ‖x‖)

Next tactic:
simpa using tendsto_id.dist (tendsto_const_nhds : Tendsto (fun _a => (1 : E)) _ _)
@[to_additive]
theorem tendsto_norm_one : Tendsto (fun a : E => ‖a‖) (𝓝 1) (𝓝 0) := by
  

Proof state:
𝓕 : Type u_1
𝕜 : Type u_2
α : Type u_3
ι : Type u_4
κ : Type u_5
E : Type u_6
F : Type u_7
G : Type u_8
inst✝² : SeminormedGroup E
inst✝¹ : SeminormedGroup F
inst✝ : SeminormedGroup G
s : Set E
a a₁ a₂ b b₁ b₂ : E
r r₁ r₂ : ℝ
⊢ Tendsto (fun a => ‖a‖) (𝓝 1) (𝓝 0)

Next tactic:
simpa using tendsto_norm_div_self (1 : E)
@[to_additive (attr := continuity) continuous_norm]
theorem continuous_norm' : Continuous fun a : E => ‖a‖ := by
  

Proof state:
𝓕 : Type u_1
𝕜 : Type u_2
α : Type u_3
ι : Type u_4
κ : Type u_5
E : Type u_6
F : Type u_7
G : Type u_8
inst✝² : SeminormedGroup E
inst✝¹ : SeminormedGroup F
inst✝ : SeminormedGroup G
s : Set E
a a₁ a₂ b b₁ b₂ : E
r r₁ r₂ : ℝ
⊢ Continuous fun a => ‖a‖

Next tactic:
simpa using continuous_id.dist (continuous_const : Continuous fun _a => (1 : E))
@[to_additive lipschitzWith_one_norm]
theorem lipschitzWith_one_norm' : LipschitzWith 1 (norm : E → ℝ) := by
  

Proof state:
𝓕 : Type u_1
𝕜 : Type u_2
α : Type u_3
ι : Type u_4
κ : Type u_5
E : Type u_6
F : Type u_7
G : Type u_8
inst✝² : SeminormedGroup E
inst✝¹ : SeminormedGroup F
inst✝ : SeminormedGroup G
s : Set E
a a₁ a₂ b b₁ b₂ : E
r r₁ r₂ : ℝ
⊢ LipschitzWith 1 norm

Next tactic:
simpa only [dist_one_left] using LipschitzWith.dist_right (1 : E)
@[to_additive]
theorem mem_closure_one_iff_norm {x : E} : x ∈ closure ({1} : Set E) ↔ ‖x‖ = 0 := by
  

Proof state:
𝓕 : Type u_1
𝕜 : Type u_2
α : Type u_3
ι : Type u_4
κ : Type u_5
E : Type u_6
F : Type u_7
G : Type u_8
inst✝² : SeminormedGroup E
inst✝¹ : SeminormedGroup F
inst✝ : SeminormedGroup G
s : Set E
a a₁ a₂ b b₁ b₂ : E
r r₁ r₂ : ℝ
x : E
⊢ x ∈ closure {1} ↔ ‖x‖ = 0

Next tactic:
rw [← closedBall_zero', mem_closedBall_one_iff, (norm_nonneg' x).le_iff_eq]
/-- A helper lemma used to prove that the (scalar or usual) product of a function that tends to one
and a bounded function tends to one. This lemma is formulated for any binary operation
`op : E → F → G` with an estimate `‖op x y‖ ≤ A * ‖x‖ * ‖y‖` for some constant A instead of
multiplication so that it can be applied to `(*)`, `flip (*)`, `(•)`, and `flip (•)`. -/
@[to_additive "A helper lemma used to prove that the (scalar or usual) product of a function that
tends to zero and a bounded function tends to zero. This lemma is formulated for any binary
operation `op : E → F → G` with an estimate `‖op x y‖ ≤ A * ‖x‖ * ‖y‖` for some constant A instead
of multiplication so that it can be applied to `(*)`, `flip (*)`, `(•)`, and `flip (•)`."]
theorem Filter.Tendsto.op_one_isBoundedUnder_le' {f : α → E} {g : α → F} {l : Filter α}
    (hf : Tendsto f l (𝓝 1)) (hg : IsBoundedUnder (· ≤ ·) l (norm ∘ g)) (op : E → F → G)
    (h_op : ∃ A, ∀ x y, ‖op x y‖ ≤ A * ‖x‖ * ‖y‖) : Tendsto (fun x => op (f x) (g x)) l (𝓝 1) := by
  

Proof state:
𝓕 : Type u_1
𝕜 : Type u_2
α : Type u_3
ι : Type u_4
κ : Type u_5
E : Type u_6
F : Type u_7
G : Type u_8
inst✝² : SeminormedGroup E
inst✝¹ : SeminormedGroup F
inst✝ : SeminormedGroup G
s : Set E
a a₁ a₂ b b₁ b₂ : E
r r₁ r₂ : ℝ
f : α → E
g : α → F
l : Filter α
hf : Tendsto f l (𝓝 1)
hg : IsBoundedUnder (fun x x_1 => x ≤ x_1) l (norm ∘ g)
op : E → F → G
h_op : ∃ A, ∀ (x : E) (y : F), ‖op x y‖ ≤ A * ‖x‖ * ‖y‖
⊢ Tendsto (fun x => op (f x) (g x)) l (𝓝 1)

Next tactic:
cases' h_op with A h_op
/-- A helper lemma used to prove that the (scalar or usual) product of a function that tends to one
and a bounded function tends to one. This lemma is formulated for any binary operation
`op : E → F → G` with an estimate `‖op x y‖ ≤ A * ‖x‖ * ‖y‖` for some constant A instead of
multiplication so that it can be applied to `(*)`, `flip (*)`, `(•)`, and `flip (•)`. -/
@[to_additive "A helper lemma used to prove that the (scalar or usual) product of a function that
tends to zero and a bounded function tends to zero. This lemma is formulated for any binary
operation `op : E → F → G` with an estimate `‖op x y‖ ≤ A * ‖x‖ * ‖y‖` for some constant A instead
of multiplication so that it can be applied to `(*)`, `flip (*)`, `(•)`, and `flip (•)`."]
theorem Filter.Tendsto.op_one_isBoundedUnder_le' {f : α → E} {g : α → F} {l : Filter α}
    (hf : Tendsto f l (𝓝 1)) (hg : IsBoundedUnder (· ≤ ·) l (norm ∘ g)) (op : E → F → G)
    (h_op : ∃ A, ∀ x y, ‖op x y‖ ≤ A * ‖x‖ * ‖y‖) : Tendsto (fun x => op (f x) (g x)) l (𝓝 1) := by
  cases' h_op with A h_op
  

Proof state:
case intro
𝓕 : Type u_1
𝕜 : Type u_2
α : Type u_3
ι : Type u_4
κ : Type u_5
E : Type u_6
F : Type u_7
G : Type u_8
inst✝² : SeminormedGroup E
inst✝¹ : SeminormedGroup F
inst✝ : SeminormedGroup G
s : Set E
a a₁ a₂ b b₁ b₂ : E
r r₁ r₂ : ℝ
f : α → E
g : α → F
l : Filter α
hf : Tendsto f l (𝓝 1)
hg : IsBoundedUnder (fun x x_1 => x ≤ x_1) l (norm ∘ g)
op : E → F → G
A : ℝ
h_op : ∀ (x : E) (y : F), ‖op x y‖ ≤ A * ‖x‖ * ‖y‖
⊢ Tendsto (fun x => op (f x) (g x)) l (𝓝 1)

Next tactic:
rcases hg with ⟨C, hC⟩
/-- A helper lemma used to prove that the (scalar or usual) product of a function that tends to one
and a bounded function tends to one. This lemma is formulated for any binary operation
`op : E → F → G` with an estimate `‖op x y‖ ≤ A * ‖x‖ * ‖y‖` for some constant A instead of
multiplication so that it can be applied to `(*)`, `flip (*)`, `(•)`, and `flip (•)`. -/
@[to_additive "A helper lemma used to prove that the (scalar or usual) product of a function that
tends to zero and a bounded function tends to zero. This lemma is formulated for any binary
operation `op : E → F → G` with an estimate `‖op x y‖ ≤ A * ‖x‖ * ‖y‖` for some constant A instead
of multiplication so that it can be applied to `(*)`, `flip (*)`, `(•)`, and `flip (•)`."]
theorem Filter.Tendsto.op_one_isBoundedUnder_le' {f : α → E} {g : α → F} {l : Filter α}
    (hf : Tendsto f l (𝓝 1)) (hg : IsBoundedUnder (· ≤ ·) l (norm ∘ g)) (op : E → F → G)
    (h_op : ∃ A, ∀ x y, ‖op x y‖ ≤ A * ‖x‖ * ‖y‖) : Tendsto (fun x => op (f x) (g x)) l (𝓝 1) := by
  cases' h_op with A h_op
  rcases hg with ⟨C, hC⟩; 

Proof state:
case intro.intro
𝓕 : Type u_1
𝕜 : Type u_2
α : Type u_3
ι : Type u_4
κ : Type u_5
E : Type u_6
F : Type u_7
G : Type u_8
inst✝² : SeminormedGroup E
inst✝¹ : SeminormedGroup F
inst✝ : SeminormedGroup G
s : Set E
a a₁ a₂ b b₁ b₂ : E
r r₁ r₂ : ℝ
f : α → E
g : α → F
l : Filter α
hf : Tendsto f l (𝓝 1)
op : E → F → G
A : ℝ
h_op : ∀ (x : E) (y : F), ‖op x y‖ ≤ A * ‖x‖ * ‖y‖
C : ℝ
hC : ∀ᶠ (x : ℝ) in map (norm ∘ g) l, (fun x x_1 => x ≤ x_1) x C
⊢ Tendsto (fun x => op (f x) (g x)) l (𝓝 1)

Next tactic:
rw [eventually_map] at hC
/-- A helper lemma used to prove that the (scalar or usual) product of a function that tends to one
and a bounded function tends to one. This lemma is formulated for any binary operation
`op : E → F → G` with an estimate `‖op x y‖ ≤ A * ‖x‖ * ‖y‖` for some constant A instead of
multiplication so that it can be applied to `(*)`, `flip (*)`, `(•)`, and `flip (•)`. -/
@[to_additive "A helper lemma used to prove that the (scalar or usual) product of a function that
tends to zero and a bounded function tends to zero. This lemma is formulated for any binary
operation `op : E → F → G` with an estimate `‖op x y‖ ≤ A * ‖x‖ * ‖y‖` for some constant A instead
of multiplication so that it can be applied to `(*)`, `flip (*)`, `(•)`, and `flip (•)`."]
theorem Filter.Tendsto.op_one_isBoundedUnder_le' {f : α → E} {g : α → F} {l : Filter α}
    (hf : Tendsto f l (𝓝 1)) (hg : IsBoundedUnder (· ≤ ·) l (norm ∘ g)) (op : E → F → G)
    (h_op : ∃ A, ∀ x y, ‖op x y‖ ≤ A * ‖x‖ * ‖y‖) : Tendsto (fun x => op (f x) (g x)) l (𝓝 1) := by
  cases' h_op with A h_op
  rcases hg with ⟨C, hC⟩; rw [eventually_map] at hC
  

Proof state:
case intro.intro
𝓕 : Type u_1
𝕜 : Type u_2
α : Type u_3
ι : Type u_4
κ : Type u_5
E : Type u_6
F : Type u_7
G : Type u_8
inst✝² : SeminormedGroup E
inst✝¹ : SeminormedGroup F
inst✝ : SeminormedGroup G
s : Set E
a a₁ a₂ b b₁ b₂ : E
r r₁ r₂ : ℝ
f : α → E
g : α → F
l : Filter α
hf : Tendsto f l (𝓝 1)
op : E → F → G
A : ℝ
h_op : ∀ (x : E) (y : F), ‖op x y‖ ≤ A * ‖x‖ * ‖y‖
C : ℝ
hC : ∀ᶠ (a : α) in l, (fun x x_1 => x ≤ x_1) ((norm ∘ g) a) C
⊢ Tendsto (fun x => op (f x) (g x)) l (𝓝 1)

Next tactic:
rw [NormedCommGroup.tendsto_nhds_one] at hf ⊢
/-- A helper lemma used to prove that the (scalar or usual) product of a function that tends to one
and a bounded function tends to one. This lemma is formulated for any binary operation
`op : E → F → G` with an estimate `‖op x y‖ ≤ A * ‖x‖ * ‖y‖` for some constant A instead of
multiplication so that it can be applied to `(*)`, `flip (*)`, `(•)`, and `flip (•)`. -/
@[to_additive "A helper lemma used to prove that the (scalar or usual) product of a function that
tends to zero and a bounded function tends to zero. This lemma is formulated for any binary
operation `op : E → F → G` with an estimate `‖op x y‖ ≤ A * ‖x‖ * ‖y‖` for some constant A instead
of multiplication so that it can be applied to `(*)`, `flip (*)`, `(•)`, and `flip (•)`."]
theorem Filter.Tendsto.op_one_isBoundedUnder_le' {f : α → E} {g : α → F} {l : Filter α}
    (hf : Tendsto f l (𝓝 1)) (hg : IsBoundedUnder (· ≤ ·) l (norm ∘ g)) (op : E → F → G)
    (h_op : ∃ A, ∀ x y, ‖op x y‖ ≤ A * ‖x‖ * ‖y‖) : Tendsto (fun x => op (f x) (g x)) l (𝓝 1) := by
  cases' h_op with A h_op
  rcases hg with ⟨C, hC⟩; rw [eventually_map] at hC
  rw [NormedCommGroup.tendsto_nhds_one] at hf ⊢
  

Proof state:
case intro.intro
𝓕 : Type u_1
𝕜 : Type u_2
α : Type u_3
ι : Type u_4
κ : Type u_5
E : Type u_6
F : Type u_7
G : Type u_8
inst✝² : SeminormedGroup E
inst✝¹ : SeminormedGroup F
inst✝ : SeminormedGroup G
s : Set E
a a₁ a₂ b b₁ b₂ : E
r r₁ r₂ : ℝ
f : α → E
g : α → F
l : Filter α
hf : ∀ ε > 0, ∀ᶠ (x : α) in l, ‖f x‖ < ε
op : E → F → G
A : ℝ
h_op : ∀ (x : E) (y : F), ‖op x y‖ ≤ A * ‖x‖ * ‖y‖
C : ℝ
hC : ∀ᶠ (a : α) in l, (fun x x_1 => x ≤ x_1) ((norm ∘ g) a) C
⊢ ∀ ε > 0, ∀ᶠ (x : α) in l, ‖op (f x) (g x)‖ < ε

Next tactic:
intro ε ε₀
/-- A helper lemma used to prove that the (scalar or usual) product of a function that tends to one
and a bounded function tends to one. This lemma is formulated for any binary operation
`op : E → F → G` with an estimate `‖op x y‖ ≤ A * ‖x‖ * ‖y‖` for some constant A instead of
multiplication so that it can be applied to `(*)`, `flip (*)`, `(•)`, and `flip (•)`. -/
@[to_additive "A helper lemma used to prove that the (scalar or usual) product of a function that
tends to zero and a bounded function tends to zero. This lemma is formulated for any binary
operation `op : E → F → G` with an estimate `‖op x y‖ ≤ A * ‖x‖ * ‖y‖` for some constant A instead
of multiplication so that it can be applied to `(*)`, `flip (*)`, `(•)`, and `flip (•)`."]
theorem Filter.Tendsto.op_one_isBoundedUnder_le' {f : α → E} {g : α → F} {l : Filter α}
    (hf : Tendsto f l (𝓝 1)) (hg : IsBoundedUnder (· ≤ ·) l (norm ∘ g)) (op : E → F → G)
    (h_op : ∃ A, ∀ x y, ‖op x y‖ ≤ A * ‖x‖ * ‖y‖) : Tendsto (fun x => op (f x) (g x)) l (𝓝 1) := by
  cases' h_op with A h_op
  rcases hg with ⟨C, hC⟩; rw [eventually_map] at hC
  rw [NormedCommGroup.tendsto_nhds_one] at hf ⊢
  intro ε ε₀
  

Proof state:
case intro.intro
𝓕 : Type u_1
𝕜 : Type u_2
α : Type u_3
ι : Type u_4
κ : Type u_5
E : Type u_6
F : Type u_7
G : Type u_8
inst✝² : SeminormedGroup E
inst✝¹ : SeminormedGroup F
inst✝ : SeminormedGroup G
s : Set E
a a₁ a₂ b b₁ b₂ : E
r r₁ r₂ : ℝ
f : α → E
g : α → F
l : Filter α
hf : ∀ ε > 0, ∀ᶠ (x : α) in l, ‖f x‖ < ε
op : E → F → G
A : ℝ
h_op : ∀ (x : E) (y : F), ‖op x y‖ ≤ A * ‖x‖ * ‖y‖
C : ℝ
hC : ∀ᶠ (a : α) in l, (fun x x_1 => x ≤ x_1) ((norm ∘ g) a) C
ε : ℝ
ε₀ : ε > 0
⊢ ∀ᶠ (x : α) in l, ‖op (f x) (g x)‖ < ε

Next tactic:
rcases exists_pos_mul_lt ε₀ (A * C) with ⟨δ, δ₀, hδ⟩
/-- A helper lemma used to prove that the (scalar or usual) product of a function that tends to one
and a bounded function tends to one. This lemma is formulated for any binary operation
`op : E → F → G` with an estimate `‖op x y‖ ≤ A * ‖x‖ * ‖y‖` for some constant A instead of
multiplication so that it can be applied to `(*)`, `flip (*)`, `(•)`, and `flip (•)`. -/
@[to_additive "A helper lemma used to prove that the (scalar or usual) product of a function that
tends to zero and a bounded function tends to zero. This lemma is formulated for any binary
operation `op : E → F → G` with an estimate `‖op x y‖ ≤ A * ‖x‖ * ‖y‖` for some constant A instead
of multiplication so that it can be applied to `(*)`, `flip (*)`, `(•)`, and `flip (•)`."]
theorem Filter.Tendsto.op_one_isBoundedUnder_le' {f : α → E} {g : α → F} {l : Filter α}
    (hf : Tendsto f l (𝓝 1)) (hg : IsBoundedUnder (· ≤ ·) l (norm ∘ g)) (op : E → F → G)
    (h_op : ∃ A, ∀ x y, ‖op x y‖ ≤ A * ‖x‖ * ‖y‖) : Tendsto (fun x => op (f x) (g x)) l (𝓝 1) := by
  cases' h_op with A h_op
  rcases hg with ⟨C, hC⟩; rw [eventually_map] at hC
  rw [NormedCommGroup.tendsto_nhds_one] at hf ⊢
  intro ε ε₀
  rcases exists_pos_mul_lt ε₀ (A * C) with ⟨δ, δ₀, hδ⟩
  

Proof state:
case intro.intro.intro.intro
𝓕 : Type u_1
𝕜 : Type u_2
α : Type u_3
ι : Type u_4
κ : Type u_5
E : Type u_6
F : Type u_7
G : Type u_8
inst✝² : SeminormedGroup E
inst✝¹ : SeminormedGroup F
inst✝ : SeminormedGroup G
s : Set E
a a₁ a₂ b b₁ b₂ : E
r r₁ r₂ : ℝ
f : α → E
g : α → F
l : Filter α
hf : ∀ ε > 0, ∀ᶠ (x : α) in l, ‖f x‖ < ε
op : E → F → G
A : ℝ
h_op : ∀ (x : E) (y : F), ‖op x y‖ ≤ A * ‖x‖ * ‖y‖
C : ℝ
hC : ∀ᶠ (a : α) in l, (fun x x_1 => x ≤ x_1) ((norm ∘ g) a) C
ε : ℝ
ε₀ : ε > 0
δ : ℝ
δ₀ : 0 < δ
hδ : A * C * δ < ε
⊢ ∀ᶠ (x : α) in l, ‖op (f x) (g x)‖ < ε

Next tactic:
filter_upwards [hf δ δ₀, hC] with i hf hg
/-- A helper lemma used to prove that the (scalar or usual) product of a function that tends to one
and a bounded function tends to one. This lemma is formulated for any binary operation
`op : E → F → G` with an estimate `‖op x y‖ ≤ A * ‖x‖ * ‖y‖` for some constant A instead of
multiplication so that it can be applied to `(*)`, `flip (*)`, `(•)`, and `flip (•)`. -/
@[to_additive "A helper lemma used to prove that the (scalar or usual) product of a function that
tends to zero and a bounded function tends to zero. This lemma is formulated for any binary
operation `op : E → F → G` with an estimate `‖op x y‖ ≤ A * ‖x‖ * ‖y‖` for some constant A instead
of multiplication so that it can be applied to `(*)`, `flip (*)`, `(•)`, and `flip (•)`."]
theorem Filter.Tendsto.op_one_isBoundedUnder_le' {f : α → E} {g : α → F} {l : Filter α}
    (hf : Tendsto f l (𝓝 1)) (hg : IsBoundedUnder (· ≤ ·) l (norm ∘ g)) (op : E → F → G)
    (h_op : ∃ A, ∀ x y, ‖op x y‖ ≤ A * ‖x‖ * ‖y‖) : Tendsto (fun x => op (f x) (g x)) l (𝓝 1) := by
  cases' h_op with A h_op
  rcases hg with ⟨C, hC⟩; rw [eventually_map] at hC
  rw [NormedCommGroup.tendsto_nhds_one] at hf ⊢
  intro ε ε₀
  rcases exists_pos_mul_lt ε₀ (A * C) with ⟨δ, δ₀, hδ⟩
  filter_upwards [hf δ δ₀, hC] with i hf hg
  

Proof state:
case h
𝓕 : Type u_1
𝕜 : Type u_2
α : Type u_3
ι : Type u_4
κ : Type u_5
E : Type u_6
F : Type u_7
G : Type u_8
inst✝² : SeminormedGroup E
inst✝¹ : SeminormedGroup F
inst✝ : SeminormedGroup G
s : Set E
a a₁ a₂ b b₁ b₂ : E
r r₁ r₂ : ℝ
f : α → E
g : α → F
l : Filter α
hf✝ : ∀ ε > 0, ∀ᶠ (x : α) in l, ‖f x‖ < ε
op : E → F → G
A : ℝ
h_op : ∀ (x : E) (y : F), ‖op x y‖ ≤ A * ‖x‖ * ‖y‖
C : ℝ
hC : ∀ᶠ (a : α) in l, (fun x x_1 => x ≤ x_1) ((norm ∘ g) a) C
ε : ℝ
ε₀ : ε > 0
δ : ℝ
δ₀ : 0 < δ
hδ : A * C * δ < ε
i : α
hf : ‖f i‖ < δ
hg : (norm ∘ g) i ≤ C
⊢ ‖op (f i) (g i)‖ < ε

Next tactic:
refine' (h_op _ _).trans_lt _